Soil Biota Reduce Allelopathic Effects of the Invasive Eupatorium adenophorum

Allelopathy has been hypothesized to play a role in exotic plant invasions, and study of this process can improve our understanding of how direct and indirect plant interactions influence plant community organization and ecosystem functioning. However, allelopathic effects can be highly conditional. For example allelopathic effects demonstrated in vivo can be difficult to demonstrate in field soils. Here we tested phytotoxicity of Eupatorium adenophorum (croftonweed), one of the most destructive exotic species in China, to a native plant species Brassica rapa both in sand and in native soil. Our results suggested that natural soils from different invaded habitats alleviated or eliminated the efficacy of potential allelochemicals relative to sand cultures. When that soil is sterilized, the allelopathic effects returned; suggesting that soil biota were responsible for the reduced phytotoxicity in natural soils. Neither of the two allelopathic compounds (9-Oxo-10,11-dehydroageraphorone and 9b-Hydroxyageraphorone) of E. adenophorum could be found in natural soils infested by the invader, and when those compounds were added to the soils as leachates, they showed substantial degradation after 24 hours in natural soils but not in sand. Our findings emphasize that soil biota can reduce the allelopathic effects of invaders on other plants, and therefore can reduce community invasibility. These results also suggest that soil biota may have stronger or weaker effects on allelopathic interactions depending on how allelochemicals are delivered

Surrounding species diversity improves subtropical seedlings’ carbon dynamics

Increasing biodiversity has been linked to higher primary productivity in terrestrial ecosystems. However, the underlying ecophysiological mechanisms remain poorly understood. We investigated the effects of surrounding species richness (monoculture, two- and four-species mixtures) on the ecophysiology of Lithocarpus glaber seedlings in experimental plots in subtropical China. A natural rain event isotopically labelled both the water uptaken by the L. glaber seedlings and the carbon in new photoassimilates through changes of photosynthetic discrimination. We followed the labelled carbon (C) and oxygen (O) in the plant–soil–atmosphere continuum. We measured gas-exchange variables (C assimilation, transpiration and above- and belowground respiration) and δ13C in leaf biomass, phloem, soil microbial biomass, leaf- and soil-respired CO2 as well as δ18O in leaf and xylem water. The 13C signal in phloem and respired CO2 in L. glaber in monoculture lagged behind those in species mixture, showing a slower transport of new photoassimilates to and through the phloem in monoculture. Furthermore, leaf-water 18O enrichment above the xylem water in L. glaber increased after the rain in lower diversity plots suggesting a lower ability to compensate for increased transpiration. Lithocarpus glaber in monoculture showed higher C assimilation rate and water-use efficiency. However, these increased C resources did not translate in higher growth of L. glaber in monoculture suggesting the existence of larger nongrowth-related C sinks in monoculture. These ecophysiological responses of L. glaber, in agreement with current understanding of phloem transport are consistent with a stronger competition for water resources in monoculture than in species mixtures. Therefore, increasing species diversity in the close vicinity of the studied plants appears to alleviate physiological stress induced by water competition and to counterbalance the negative effects of interspecific competition on assimilation rates for L. glaber by allowing a higher fraction of the C assimilated to be allocated to growth in species mixture than in monoculture

Surrounding species diversity improves subtropical seedlings’ carbon dynamics

Increasing biodiversity has been linked to higher primary productivity in terrestrial ecosystems. However, the underlying ecophysiological mechanisms remain poorly understood. We investigated the effects of surrounding species richness (monoculture, two- and four-species mixtures) on the ecophysiology of Lithocarpus glaber seedlings in experimental plots in subtropical China. A natural rain event isotopically labelled both the water uptaken by the L.glaber seedlings and the carbon in new photoassimilates through changes of photosynthetic discrimination. We followed the labelled carbon (C) and oxygen (O) in the plant-soil-atmosphere continuum. We measured gas-exchange variables (C assimilation, transpiration and above- and belowground respiration) and C-13 in leaf biomass, phloem, soil microbial biomass, leaf- and soil-respired CO2 as well as O-18 in leaf and xylem water. The C-13 signal in phloem and respired CO2 in L.glaber in monoculture lagged behind those in species mixture, showing a slower transport of new photoassimilates to and through the phloem in monoculture. Furthermore, leaf-water O-18 enrichment above the xylem water in L.glaber increased after the rain in lower diversity plots suggesting a lower ability to compensate for increased transpiration. Lithocarpus glaber in monoculture showed higher C assimilation rate and water-use efficiency. However, these increased C resources did not translate in higher growth of L.glaber in monoculture suggesting the existence of larger nongrowth-related C sinks in monoculture. These ecophysiological responses of L.glaber, in agreement with current understanding of phloem transport are consistent with a stronger competition for water resources in monoculture than in species mixtures. Therefore, increasing species diversity in the close vicinity of the studied plants appears to alleviate physiological stress induced by water competition and to counterbalance the negative effects of interspecific competition on assimilation rates for L.glaber by allowing a higher fraction of the C assimilated to be allocated to growth in species mixture than in monoculture.Peer reviewe

‘openDS’ – A new standard for digital specimens and other natural science digital object types

With projected lifespans of many decades, infrastructure initiatives such as Europe’s Distributed System of Scientific Collections (DiSSCo), USA’s Integrated Digitized Biocollections (iDigBio), National Specimen Information Infrastructure (NSII) of China and Australia’s digitisation of national research collections (NRCA Digital) aim at transforming today’s slow, inefficient and limited practices of working with natural science collections. The need to borrow specimens (plants, animals, fossils or rocks) or physically visit collections, and absence of linkages to other relevant information represent significant impediments to answering today’s scientific and societal questions. A logical extension of the Internet, Digital Object Architecture (Kahn and Wilensky 2006) offers a way of grouping, managing and processing fragments of information relating to a natural science specimen. A ‘digital specimen’ acts as a surrogate in cyberspace for a specific physical specimen, identifying its actual location and authoritatively saying something about its collection event (who, when, where) and taxonomy, as well as providing links to high-resolution images. A digital specimen exposes supplementary information about related literature, traits, tissue samples and DNA sequences, chemical analyses, environmental information, etc. stored elsewhere than in the natural science collection itself. By presenting digital specimens as a new layer between data infrastructure of natural science collections and user applications for processing and interacting with information about specimens and collections, it’s possible to seamlessly organise global access spanning multiple collection-holding institutions and sources. Virtual collections of digital specimens with unique identifiers offer possibilities for wider, more flexible, and ‘FAIR’ (Findable, Accessible, Interoperable, Reusable) access for varied research and policy uses: recognising curatorial work, annotating with latest taxonomic treatments, understanding variations, working with DNA sequences or chemical analyses, supporting regulatory processes for health, food, security, sustainability and environmental change, inventions/products critical to the bio-economy, and educational uses. Adopting a digital specimen approach is expected to lead to faster insights for lower cost on many fronts. We propose that realising this vision requires a new TDWG standard. OpenDS is a specification of digital specimen and other object types essential to mass digitisation of natural science collections and their digital use. For five principal digital object types corresponding to major categories of collections and specimens’ information, OpenDS defines structure and content, and behaviours that can act upon them: 1. Digital specimen: Representing a digitised physical specimen, contains information about a single specimen with links to related supplementary information; 2. Storage container: Representing groups of specimens stored within a single container, such as insect tray, drawer or sample jar; 3. Collection: Information about characteristics of a collection; 4. Organisation: Information about the legal-entity owning the specimen and collection to which it belongs; and, 5. Interpretation: Assertion(s) made on or about the specimen such as determination of species and comments. Secondary classes gather presentation/preservation characteristics (e.g., herbarium sheets, pinned insects, specimens in glass jars, etc.), the general classification of a specimen (i.e., plant, animal, fossil, rock, etc.) and history of actions on the object (provenance). Equivalencing concepts in ABCD 3.0 and EFG extension for geo-sciences, OpenDS is also an ontology extending OBO Foundry’s Biological Collection Ontology (BCO) (Walls et al. 2014) from bco:MaterialSample, which has preferred label dwc:specimen from Darwin Core, thus linking it also with that standard. OpenDS object content can be serialized to specific formats/representations (e.g. JSON) for different exchange and processing purposes

Pre-training with Aspect-Content Text Mutual Prediction for Multi-Aspect Dense Retrieval

Grounded on pre-trained language models (PLMs), dense retrieval has been studied extensively on plain text. In contrast, there has been little research on retrieving data with multiple aspects using dense models. In the scenarios such as product search, the aspect information plays an essential role in relevance matching, e.g., category: Electronics, Computers, and Pet Supplies. A common way of leveraging aspect information for multi-aspect retrieval is to introduce an auxiliary classification objective, i.e., using item contents to predict the annotated value IDs of item aspects. However, by learning the value embeddings from scratch, this approach may not capture the various semantic similarities between the values sufficiently. To address this limitation, we leverage the aspect information as text strings rather than class IDs during pre-training so that their semantic similarities can be naturally captured in the PLMs. To facilitate effective retrieval with the aspect strings, we propose mutual prediction objectives between the text of the item aspect and content. In this way, our model makes more sufficient use of aspect information than conducting undifferentiated masked language modeling (MLM) on the concatenated text of aspects and content. Extensive experiments on two real-world datasets (product and mini-program search) show that our approach can outperform competitive baselines both treating aspect values as classes and conducting the same MLM for aspect and content strings. Code and related dataset will be available at the URL \footnote{https://github.com/sunxiaojie99/ATTEMPT}.Comment: accepted by cikm202

Effects of enemy exclusion on biodiversity–productivity relationships in a subtropical forest experiment

Interspecific niche complementarity is a key mechanism posited to explain positive species richness–productivity relationships in plant communities. However, the exact nature of the niche dimensions that plant species partition remains poorly known. Species may partition abiotic resources that limit their growth, but species may also be specialized with respect to their set of biotic interactions with other trophic levels, in particular with enemies including pathogens and consumers. The lower host densities present in more species-diverse plant communities may therefore result in smaller populations of specialized enemies, and in a smaller associated negative feedback these enemies exert on plant productivity. To test whether such host density-dependent effects of enemies drive diversity–productivity relationships in young forest stands, we experimentally manipulated leaf fungal pathogens and insect herbivores in a large subtropical forest biodiversity–ecosystem functioning experiment in China (BEF-China). We found that fungicide spraying of tree canopies removed the positive tree-species richness–productivity relationship present in untreated control plots. The tree species that contributed the most to this effect were the ones with the highest fungicide-induced growth increase in monoculture. Insecticide application did not cause comparable effects. Synthesis. Our findings suggest that tree species diversity may not only promote productivity by interspecific resource-niche partitioning but also by trophic niche partitioning. Most likely, partitioning occurred with respect to enemies such as pathogenic fungi. Alternatively, similar effects on tree growth would have occurred if fungicide had eliminated positive effects of a higher diversity of beneficial fungi (e.g. mycorrhizal symbionts) that may have occurred in mixed tree species communities

Global Priority Conservation Areas in the Face of 21st Century Climate Change

In an era when global biodiversity is increasingly impacted by rapidly changing climate, efforts to conserve global biodiversity may be compromised if we do not consider the uneven distribution of climate-induced threats. Here, via a novel application of an aggregate Regional Climate Change Index (RCCI) that combines changes in mean annual temperature and precipitation with changes in their interannual variability, we assess multi-dimensional climate changes across the “Global 200” ecoregions – a set of priority ecoregions designed to “achieve the goal of saving a broad diversity of the Earth’s ecosystems” – over the 21st century. Using an ensemble of 62 climate scenarios, our analyses show that, between 1991–2010 and 2081–2100, 96% of the ecoregions considered will be likely (more than 66% probability) to face moderate-to-pronounced climate changes, when compared to the magnitudes of change during the past five decades. Ecoregions at high northern latitudes are projected to experience most pronounced climate change, followed by those in the Mediterranean Basin, Amazon Basin, East Africa, and South Asia. Relatively modest RCCI signals are expected over ecoregions in Northwest South America, West Africa, and Southeast Asia, yet with considerable uncertainties. Although not indicative of climate-change impacts per se, the RCCI-based assessment can help policy-makers gain a quantitative and comprehensive overview of the unevenly distributed climate risks across the G200 ecoregions. Whether due to significant climate change signals or large uncertainties, the ecoregions highlighted in the assessment deserve special attention in more detailed impact assessments to inform effective conservation strategies under future climate change.This study was supported by the Environmental Protection Public Service Project of China (201209031) (URL:http://kjs.mep.gov.cn/gyxhykyzx/)

Sampling biases shape our view of the natural world

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