Species from different taxonomic groups show similar invasion traits

Invasion ecology tends to treat taxonomic groups separately. However, given that all invasive species go through the same stages of the invasion process (transport, escape, establishment, spread), it is likely that – across taxa – comparable traits help to successfully complete this process ("invasion traits"). Perhaps not all invasive species have the same invasion traits, but different combinations of invasion traits can be found among invaders, corresponding to different possibilities to become a successful invader. These combinations of invasion traits might be linked to taxonomic affiliation, but this is not necessarily the case. We created a global dataset with 201 invasive species from seven major taxonomic groups (animals, green plants, fungi, heterokonts, bacteria, red algae, alveolates) and 13 invasion traits that are applicable across all taxa. The dataset was analysed with cluster analysis to search for similarities in combinations of invasion traits. Three of the five clusters, comprising 60% of all species, contain several major taxonomic groups. While some invasion trait frequencies were significantly related to taxonomic affiliation, the results show that invasive species from different taxonomic groups often share similar combinations of invasion traits. A post-hoc analysis suggests that combinations of traits characterizing successful invaders can be associated with invasion stages across taxa. Our findings suggest that there are no universal invasion traits which could explain the invasion success of all invaders, but that invaders are successful for different reasons which are represented by different combinations of invasion traits across taxonomic groups

A conceptual map of invasion biology: Integrating hypotheses into a consensus network

Background and aims Since its emergence in the mid‐20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overlapping and, in some cases, contradictory hypotheses about biological invasions. To make these contradictions and redundancies explicit, and to gain insight into the field’s current theoretical structure, we developed and applied a Delphi approach to create a consensus network of 39 existing invasion hypotheses. Results The resulting network was analysed with a link‐clustering algorithm that revealed five concept clusters (resource availability, biotic interaction, propagule, trait and Darwin’s clusters) representing complementary areas in the theory of invasion biology. The network also displays hypotheses that link two or more clusters, called connecting hypotheses, which are important in determining network structure. The network indicates hypotheses that are logically linked either positively (77 connections of support) or negatively (that is, they contradict each other; 6 connections). Significance The network visually synthesizes how invasion biology’s predominant hypotheses are conceptually related to each other, and thus, reveals an emergent structure – a conceptual map – that can serve as a navigation tool for scholars, practitioners and students, both inside and outside of the field of invasion biology, and guide the development of a more coherent foundation of theory. Additionally, the outlined approach can be more widely applied to create a conceptual map for the larger fields of ecology and biogeography

Think globally, measure locally: The MIREN standardized protocol for monitoring plant species distributions along elevation gradients

Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non-native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non-native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series, even more exciting results can be expected, especially about range shifts. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented.EEA BarilocheFil: Haider, Sylvia. German Centre for Integrative Biodiversity Research; AlemaniaFil: Haider, Sylvia. Martin Luther University. Institute of Biology. Geobotany and Botanical Garden; AlemaniaFil: Lembrechts, Jonas Johan. University of Antwerp. Centre of Excellence Plants and Ecosystems (PLECO); BélgicaFil: McDougall, Keith. Department of Planning, Industry and Environment; AustraliaFil: Pauchard, Aníbal. Universidad de Concepción. Facultad de Ciencias Forestales. Laboratorio de Invasiones Biológicas; ChileFil: Pauchard, Aníbal. Institute of Ecology and Biodiversity (IEB); ChileFil: Alexander, Jake M. Institute of Integrative Biology; SuizaFil: Barros, Agustina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico. Instituto Argentino de Nivología y Glaciología y Ciencias Ambientales (IANIGLA); ArgentinaFil: Cavieres, Lohengrin A. Universidad de Concepción. Facultad de Ciencias Naturales y Oceanográficas. Departamento de Botánica; ChileFil: Cavieres, Lohengrin A. Institute of Ecology and Biodiversity (IEB); ChileFil: Rashid, Irfan. University of Kashmir. Department of Botany; IndiaFil: Rew, Lisa J. Montana State University. Department of Land Resource and Environmental Sciences; Estados UnidosFil: Aleksanyan, Alla. Institute of Botany aft. A.L. Takhtajyan NAS RA. Department of Geobotany and Plant Ecophysiology; ArmeniaFil: Aleksanyan, Alla. Armenian National Agrarian University. Chair of Biology and Biotechnologies; ArmeniaFil: Dimarco, Romina Daniela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. Grupo de Ecología de Poblaciones de Insectos; ArgentinaFil: Dimarco, Romina Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. Grupo de Ecología de Poblaciones de Insectos; ArgentinaFil: Dimarco, Romina Daniela. University of Houston. Department of Biology and Biochemistry; Estados UnidosFil: Seipel, Tim. Montana State University. Department of Land Resource and Environmental Sciences; Estados Unido

Towards a methodical framework for comprehensively assessing forest multifunctionality

Funded by Deutsche Forschungsgemeinschaft. Grant Number: DFG FOR 891/1-3 National Natural Science Foundation of China. Grant Numbers: 30710103907, 30930005, 31170457, 31210103910 Swiss National Science Foundation (SNSF) Sino-German Centre for Research Promotion in Beijing. Grant Number: GZ 986Peer reviewedPublisher PD

Nitrogen but not phosphorus addition affects symbiotic N2 fixation by legumes in natural and semi‑natural grasslands located on four continents

The amount of nitrogen (N) derived from symbiotic N2 fixation by legumes in grasslands might be affected by anthropogenic N and phosphorus (P) inputs, but the underlying mechanisms are not known. Methods We evaluated symbiotic N2 fixation in 17 natural and semi-natural grasslands on four continents that are subjected to the same full-factorial N and P addition experiment, using the 15N natural abundance method. Results N as well as combined N and P (NP) addition reduced aboveground legume biomass by 65% and 45%, respectively, compared to the control, whereas P addition had no significant impact. Addition of N and/or P had no significant effect on the symbiotic N2 fixation per unit legume biomass. In consequence, the amount of N fixed annually per grassland area was less than half in the N addition treatments compared to control and P addition, irrespective of whether the dominant legumes were annuals or perennials. Conclusion Our results reveal that N addition mainly impacts symbiotic N2 fixation via reduced biomass of legumes rather than changes in N2 fixation per unit legume biomass. The results show that soil N enrichment by anthropogenic activities significantly reduces N 2 fixation in grasslands, and these effects cannot be reversed by additional P amendment.EEA Santa CruzFil: Vázquez, Eduardo. University of Bayreuth. Department of Soil Ecology. Bayreuth Center of Ecology and Environmental Research (BayCEER); AlemaniaFil: Vázquez, Eduardo. Swedish University of Agricultural Sciences. Department of Soil and Environment; SueciaFil: Schleuss, Per‑Marten. University of Bayreuth. Department of Soil Ecology. Bayreuth Center of Ecology and Environmental Research (BayCEER); AlemaniaFil: Borer, Elizabeth T. University of Minnesota. Department of Ecology, Evolution, and Behavior; Estados UnidosFil: Bugalho, Miguel N. University of Lisbon. Centre for Applied Ecology “Prof. Baeta Neves” (CEABN-InBIO). School of Agriculture; Portugal.Fil: Caldeira, Maria. C. University of Lisbon. Forest Research Centre. School of Agriculture; Portugal.Fil: Eisenhauer, Nico. German Centre for Integrative Biodiversity Research; AlemaniaFil: Eisenhauer, Nico. Leipzig University. Institute of Biology; AlemaniaFil: Eskelinen, Anu. German Centre for Integrative Biodiversity Research; AlemaniaFil: Eskelinen, Anu. Physiological Diversity, Helmholtz Centrefor Environmental Research; AlemaniaFil: Eskelinen, Anu. University of Oulu. Ecology & Genetics; FinlandiaFil: Fay, Philip A. Grassland Soil and Water Research Laboratory (USDA-ARS); Estados UnidosFil: Haider, Sylvia. German Centre for Integrative Biodiversity Research; AlemaniaFil: Haider, Sylvia. Martin Luther University. Institute of Biology. Geobotany and Botanical Garden; AlemaniaFil: Jentsch, Anke. University of Bayreuth. Department of Soil Ecology. Bayreuth Center of Ecology and Environmental Research (BayCEER); AlemaniaFil: Kirkman, Kevin P. University of KwaZulu-Natal. School of Life Sciences; SudáfricaFil: McCulley, Rebecca L. University of Kentucky. Department of Plant and Soil Sciences; Estados UnidosFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Price, Jodi. Charles Sturt University. Institute for Land, Water and Society; Australia.Fil: Richards, Anna E. CSIRO Land and Water. Northern Territory; Australia.Fil: Risch, Anita C. Swiss Federal Institute for Forest, Snow and Landscape Research WSL; SuizaFil: Roscher, Christiane. German Centre for Integrative Biodiversity Research; AlemaniaFil: Roscher, Christiane. Physiological Diversity, Helmholtz Centre for Environmental Research; AlemaniaFil: Schütz, Martin. Swiss Federal Institute for Forest, Snow and Landscape Research WSL; SuizaFil: Seabloom, Eric William. University of Minnesota. Dept. of Ecology, Evolution, and Behavior; Estados UnidosFil: Standish, Rachel J. Murdoch University. Harry Butler Institute; Australia.Fil: Stevens, Carly J. Lancaster University. Lancaster Environment Centre; Reino UnidoFil: Tedder, Michelle J. University of KwaZulu-Natal. School of Life Sciences; SudáfricaFil: Virtanen, Risto. University of Oulu. Ecology & Genetics; Finlandia.Fil: Spohn, Marie. University of Bayreuth. Department of Soil Ecology. Bayreuth Center of Ecology and Environmental Research (BayCEER); AlemaniaFil: Spohn, Marie. Swedish University of Agricultural Sciences. Department of Soil and Environment; Sueci

Nitrogen but not phosphorus addition affects symbiotic N-2 fixation by legumes in natural and semi-natural grasslands located on four continents

Background and aims: The amount of nitrogen (N) derived from symbiotic N-2 fixation by legumes in grasslands might be affected by anthropogenic N and phosphorus (P) inputs, but the underlying mechanisms are not known.Methods: We evaluated symbiotic N-2 fixation in 17 natural and semi-natural grasslands on four continents that are subjected to the same full-factorial N and P addition experiment, using the N-15 natural abundance method.Results: N as well as combined N and P (NP) addition reduced aboveground legume biomass by 65% and 45%, respectively, compared to the control, whereas P addition had no significant impact. Addition of N and/or P had no significant effect on the symbiotic N-2 fixation per unit legume biomass. In consequence, the amount of N fixed annually per grassland area was less than half in the N addition treatments compared to control and P addition, irrespective of whether the dominant legumes were annuals or perennials.Conclusion: Our results reveal that N addition mainly impacts symbiotic N-2 fixation via reduced biomass of legumes rather than changes in N-2 fixation per unit legume biomass. The results show that soil N enrichment by anthropogenic activities significantly reduces N-2 fixation in grasslands, and these effects cannot be reversed by additional P amendment

The positive effect of plant diversity on soil carbon depends on climate

Little is currently known about how climate modulates the relationship between plant diversity and soil organic carbon and the mechanisms involved. Yet, this knowledge is of crucial importance in times of climate change and biodiversity loss. Here, we show that plant diversity is positively correlated with soil carbon content and soil carbon-to-nitrogen ratio across 84 grasslands on six continents that span wide climate gradients. The relationships between plant diversity and soil carbon as well as plant diversity and soil organic matter quality (carbon-to-nitrogen ratio) are particularly strong in warm and arid climates. While plant biomass is positively correlated with soil carbon, plant biomass is not significantly correlated with plant diversity. Our results indicate that plant diversity influences soil carbon storage not via the quantity of organic matter (plant biomass) inputs to soil, but through the quality of organic matter. The study implies that ecosystem management that restores plant diversity likely enhances soil carbon sequestration, particularly in warm and arid climates

Environmental heterogeneity modulates the effect of plant diversity on the spatial variability of grassland biomass

Plant productivity varies due to environmental heterogeneity, and theory suggests that plant diversity can reduce this variation. While there is strong evidence of diversity effects on temporal variability of productivity, whether this mechanism extends to variability across space remains elusive. Here we determine the relationship between plant diversity and spatial variability of productivity in 83 grasslands, and quantify the effect of experimentally increased spatial heterogeneity in environmental conditions on this relationship. We found that communities with higher plant species richness (alpha and gamma diversity) have lower spatial variability of productivity as reduced abundance of some species can be compensated for by increased abundance of other species. In contrast, high species dissimilarity among local communities (beta diversity) is positively associated with spatial variability of productivity, suggesting that changes in species composition can scale up to affect productivity. Experimentally increased spatial environmental heterogeneity weakens the effect of plant alpha and gamma diversity, and reveals that beta diversity can simultaneously decrease and increase spatial variability of productivity. Our findings unveil the generality of the diversity-stability theory across space, and suggest that reduced local diversity and biotic homogenization can affect the spatial reliability of key ecosystem functions.Fil: 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: 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: Chaneton, Enrique Jose. 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: Iribarne, Oscar Osvaldo. 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: 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: Bakker, Jonathan. University of Washington; Estados UnidosFil: Borer, Elizabeth. University of Minnesota; Estados UnidosFil: Bruschetti, Carlos Martin. 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: MacDougall, Andrew S.. University Of Guelph. Department Of Integrative Biology.; CanadáFil: Pascual, Jesus Maria. 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: Sankaran, Mahesh. University of Leeds; Reino Unido. Tata Institute of Fundamental Research; IndiaFil: Seabloom, Eric. University of Minnesota; Estados UnidosFil: Wang, Shaopeng. Peking University; ChinaFil: Bagchi, Sumanta. Indian Institute of Science; IndiaFil: Brudvig, Lars A.. Michigan State University; Estados UnidosFil: Catford, Jane A.. University of Melbourne; Australia. Kings College London (kcl);Fil: Dickman, Chris R.. The University Of Sydney; AustraliaFil: Dickson, Tymothy L.. University of Nebraska; Estados UnidosFil: Donohue, Ian. Trinity College Dublin; Reino UnidoFil: Eisenhauer, Nico. Universitat Leipzig; Alemania. German Centre for Integrative Biodiversity Research; AlemaniaFil: Gruner, Daniel S.. University of Maryland; Estados UnidosFil: Haider, Sylvia. German Centre for Integrative Biodiversity Research; Alemania. Martin Luther University Halle-Wittenberg; Alemania. Leuphana University of Lüneburg; AlemaniaFil: Jentsch, Anke. University of Bayreuth; AlemaniaFil: Knops, Johannes M. H.. Xi’an Jiaotong-Liverpool University; ChinaFil: Lekberg, Ylva. University of Montana; Estados UnidosFil: McCulley, Rebecca L.. University of Kentucky; Estados UnidosFil: Moore, Joslin L.. University of Melbourne; Australia. Monash University; Australia. Arthur Rylah Institute for Environmental Research; AustraliaFil: Mortensen, Brent. Benedictine College; Estados UnidosFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria; Argentina. Universidad Nacional de la Patagonia Austral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rocca, Camila. 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; Argentin

Global patterns and drivers of alpine plant species richness

Aim Alpine ecosystems differ in area, macroenvironment and biogeographical history across the Earth, but the relationship between these factors and plant species richness is still unexplored. Here, we assess the global patterns of plant species richness in alpine ecosystems and their association with environmental, geographical and historical factors at regional and community scales. Location Global. Time period Data collected between 1923 and 2019. Major taxa studied Vascular plants. Methods We used a dataset representative of global alpine vegetation, consisting of 8,928 plots sampled within 26 ecoregions and six biogeographical realms, to estimate regional richness using sample‐based rarefaction and extrapolation. Then, we evaluated latitudinal patterns of regional and community richness with generalized additive models. Using environmental, geographical and historical predictors from global raster layers, we modelled regional and community richness in a mixed‐effect modelling framework. Results The latitudinal pattern of regional richness peaked around the equator and at mid‐latitudes, in response to current and past alpine area, isolation and the variation in soil pH among regions. At the community level, species richness peaked at mid‐latitudes of the Northern Hemisphere, despite a considerable within‐region variation. Community richness was related to macroclimate and historical predictors, with strong effects of other spatially structured factors. Main conclusions In contrast to the well‐known latitudinal diversity gradient, the alpine plant species richness of some temperate regions in Eurasia was comparable to that of hyperdiverse tropical ecosystems, such as the páramo. The species richness of these putative hotspot regions is explained mainly by the extent of alpine area and their glacial history, whereas community richness depends on local environmental factors. Our results highlight hotspots of species richness at mid‐latitudes, indicating that the diversity of alpine plants is linked to regional idiosyncrasies and to the historical prevalence of alpine ecosystems, rather than current macroclimatic gradients

Ortho2ExpressMatrix—a web server that interprets cross-species gene expression data by gene family information

<p>Abstract</p> <p>Background</p> <p>The study of gene families is pivotal for the understanding of gene evolution across different organisms and such phylogenetic background is often used to infer biochemical functions of genes. Modern high-throughput experiments offer the possibility to analyze the entire transcriptome of an organism; however, it is often difficult to deduct functional information from that data.</p> <p>Results</p> <p>To improve functional interpretation of gene expression we introduce Ortho2ExpressMatrix, a novel tool that integrates complex gene family information, computed from sequence similarity, with comparative gene expression profiles of two pre-selected biological objects: gene families are displayed with two-dimensional matrices. Parameters of the tool are object type (two organisms, two individuals, two tissues, etc.), type of computational gene family inference, experimental meta-data, microarray platform, gene annotation level and genome build. Family information in Ortho2ExpressMatrix bases on computationally different protein family approaches such as EnsemblCompara, InParanoid, SYSTERS and Ensembl Family. Currently, respective all-against-all associations are available for five species: human, mouse, worm, fruit fly and yeast. Additionally, microRNA expression can be examined with respect to miRBase or TargetScan families. The visualization, which is typical for Ortho2ExpressMatrix, is performed as matrix view that displays functional traits of genes (differential expression) as well as sequence similarity of protein family members (BLAST e-values) in colour codes. Such translations are intended to facilitate the user's perception of the research object.</p> <p>Conclusions</p> <p>Ortho2ExpressMatrix integrates gene family information with genome-wide expression data in order to enhance functional interpretation of high-throughput analyses on diseases, environmental factors, or genetic modification or compound treatment experiments. The tool explores differential gene expression in the light of orthology, paralogy and structure of gene families up to the point of ambiguity analyses. Results can be used for filtering and prioritization in functional genomic, biomedical and systems biology applications. The web server is freely accessible at <url>http://bioinf-data.charite.de/o2em/cgi-bin/o2em.pl</url>.</p