Biodiversity regulates ecosystem functions such as productivity, and experimental studies of species mixtures have revealed selection and complementarity effects driving these responses. However, the impacts of intraspecific genotypic diversity in these studies are unknown, despite it forming a substantial part of the biodiversity. In a glasshouse experiment we constructed plant communities with different levels of barley (Hordeum vulgare) genotype and weed species diversity and assessed their relative biodiversity effects through additive partitioning into selection and complementarity effects. Barley genotype diversity had weak positive effects on aboveground biomass through complementarity effects, whereas weed species diversity increased biomass predominantly through selection effects. When combined, increasing genotype diversity of barley tended to dilute the selection effect of weeds. We interpret these different effects of barley genotype and weed species diversity as the consequence of small vs large trait variation associated with intraspecific barley diversity and interspecific weed diversity, respectively. The different effects of intra- vs interspecific diversity highlight the underestimated and overlooked role of genetic diversity for ecosystem functioning.

Download full-text PDF

Source
http://dx.doi.org/10.1111/nph.13043DOI Listing

Publication Analysis

Top Keywords

complementarity effects
12
weed species
12
species diversity
12
diversity
11
genetic diversity
8
selection complementarity
8
effects
8
genotype weed
8
effects barley
8
barley genotype
8

Similar Publications

Long non-coding RNAs (lncRNAs) are strongly associated with cellular physiological mechanisms and implicated in the numerous diseases. By exploring the subcellular localizations of lncRNAs, we can not only gain crucial insights into the molecular mechanisms of lncRNA-related biological processes but also make valuable contributions towards the diagnosis, prevention, and treatment of various human diseases. However, conventional experimental techniques tend to be laborious and time-intensive.

View Article and Find Full Text PDF

Enhancing the performance of SSVEP-based BCIs by combining task-related component analysis and deep neural network.

Sci Rep

January 2025

Department of Biomedical Engineering, School of Biomedical Engineering, Tsinghua University, Beijing, 100084, China.

Steady-State Visually Evoked Potential (SSVEP) signals can be decoded by either a traditional machine learning algorithm or a deep learning network. Combining the two methods is expected to enhance the performance of an SSVEP-based brain-computer interface (BCI) by exploiting their advantages. However, an efficient strategy for integrating the two methods has not yet been established.

View Article and Find Full Text PDF

Osteosarcoma (OS) is the most common bone malignancy. c-MET is recognized as a therapeutic target. However, traditional c-MET inhibitors show compromised efficacy due to the acquired resistance and side effects.

View Article and Find Full Text PDF

Edge-guided feature fusion network for RGB-T salient object detection.

Front Neurorobot

December 2024

Department of Information Engineering, Shanghai Maritime University, Shanghai, China.

Introduction: RGB-T Salient Object Detection (SOD) aims to accurately segment salient regions in both visible light and thermal infrared images. However, many existing methods overlook the critical complementarity between these modalities, which can enhance detection accuracy.

Methods: We propose the Edge-Guided Feature Fusion Network (EGFF-Net), which consists of cross-modal feature extraction, edge-guided feature fusion, and salience map prediction.

View Article and Find Full Text PDF

Introduction: Emotion recognition using electroencephalography (EEG) is a key aspect of brain-computer interface research. Achieving precision requires effectively extracting and integrating both spatial and temporal features. However, many studies focus on a single dimension, neglecting the interplay and complementarity of multi-feature information, and the importance of fully integrating spatial and temporal dynamics to enhance performance.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!