Grassland vertical height heterogeneity predicts flower and bee diversity: an UAV photogrammetric approach.

The ecosystem services offered by pollinators are vital for supporting agriculture and ecosystem functioning, with bees standing out as especially valuable contributors among these insects. Threats such as habitat fragmentation, intensive agriculture, and climate change are contributing to the decline of natural bee populations. Remote sensing could be a useful tool to identify sites of high diversity before investing into more expensive field survey. In this study, the ability of Unoccupied Aerial Vehicles (UAV) images to estimate biodiversity at a local scale has been assessed while testing the concept of the Height Variation Hypothesis (HVH). This hypothesis states that the higher the vegetation height heterogeneity (HH) measured by remote sensing information, the higher the vegetation vertical complexity and the associated species diversity. In this study, the concept has been further developed to understand if vegetation HH can also be considered a proxy for bee diversity and abundance. We tested this approach in 30 grasslands in the South of the Netherlands, where an intensive field data campaign (collection of flower and bee diversity and abundance) was carried out in 2021, along with a UAV campaign (collection of true color-RGB-images at high spatial resolution). Canopy Height Models (CHM) of the grasslands were derived using the photogrammetry technique "Structure from Motion" (SfM) with horizontal resolution (spatial) of 10 cm, 25 cm, and 50 cm. The accuracy of the CHM derived from UAV photogrammetry was assessed by comparing them through linear regression against local CHM LiDAR (Light Detection and Ranging) data derived from an Airborne Laser Scanner campaign completed in 2020/2021, yielding an [Formula: see text] of 0.71. Subsequently, the HH assessed on the CHMs at the three spatial resolutions, using four different heterogeneity indices (Rao's Q, Coefficient of Variation, Berger-Parker index, and Simpson's D index), was correlated with the ground-based flower and bee diversity and bee abundance data. The Rao's Q index was the most effective heterogeneity index, reaching high correlations with the ground-based data (0.44 for flower diversity, 0.47 for bee diversity, and 0.34 for bee abundance). Interestingly, the correlations were not significantly influenced by the spatial resolution of the CHM derived from UAV photogrammetry. Our results suggest that vegetation height heterogeneity can be used as a proxy for large-scale, standardized, and cost-effective inference of flower diversity and habitat quality for bees.

Geographical patterns of root nodule bacterial diversity in cultivated and wild populations of a woody legume crop.

There is interest in understanding how cultivation, plant genotype, climate and soil conditions influence the biogeography of root nodule bacterial communities of legumes. For crops from regions with relict wild populations, this is of even greater interest because the effects of cultivation on symbiont communities can be revealed, which is of particular interest for bacteria such as rhizobia. Here, we determined the structure of root nodule bacterial communities of rooibos (Aspalathus linearis), a leguminous shrub endemic to South Africa. We related the community dissimilarities of the root nodule bacteria of 18 paired cultivated and wild rooibos populations to pairwise geographical distances, plant ecophysiological characteristics and soil physicochemical parameters. Using next-generation sequencing data, we identified region-, cultivation- and farm-specific operational taxonomic units for four distinct classes of root nodule bacterial communities, dominated by members of the genus Mesorhizobium. We found that while bacterial richness was locally increased by organic cultivation, strong biogeographical differentiation in the bacterial communities of wild rooibos disappeared with cultivation of one single cultivar across its entire cultivation range. This implies that expanding rooibos farming has the potential to endanger wild rooibos populations through the homogenisation of root nodule bacterial diversity.

Experimental assembly reveals ecological drift as a major driver of root nodule bacterial diversity in a woody legume crop.

Understanding how plant-associated microbial communities assemble and the role they play in plant performance are major goals in microbial ecology. For nitrogen-fixing rhizobia, community assembly is generally driven by host plant selection and soil conditions. Here, we aimed to determine the relative importance of neutral and deterministic processes in the assembly of bacterial communities of root nodules of a legume shrub adapted to extreme nutrient limitation, rooibos (Aspalathus linearis Burm. Dahlgren). We grew rooibos seedlings in soil from cultivated land and wild habitats, and mixtures of these soils, sampled from a wide geographic area, and with a fertilization treatment. Bacterial communities were characterized using next generation sequencing of part of the nodA gene (i.e. common to the core rhizobial symbionts of rooibos), and part of the gyrB gene (i.e. common to all bacterial taxa). Ecological drift alone was a major driver of taxonomic turnover in the bacterial communities of root nodules (62.6% of gyrB communities). In contrast, the assembly of core rhizobial communities (genus Mesorhizobium) was driven by dispersal limitation in concert with drift (81.1% of nodA communities). This agrees with a scenario of rooibos-Mesorhizobium specificity in spatially separated subpopulations, and low host filtering of other bacteria colonizing root nodules in a stochastic manner.

Insights from invasion ecology: Can consideration of eco-evolutionary experience promote benefits from root mutualisms in plant production?

Mutualistic plant-microbial functioning relies on co-adapted symbiotic partners as well as conducive environmental conditions. Choosing particular plant genotypes for domestication and subsequent cultivar selection can narrow the gene pools of crop plants to a degree that they are no longer able to benefit from microbial mutualists. Elevated mineral nutrient levels in cultivated soils also reduce the dependence of crops on nutritional support by mutualists such as mycorrhizal fungi and rhizobia. Thus, current ways of crop production are predestined to compromise the propagation and function of microbial symbionts, limiting their long-term benefits for plant yield stability. The influence of mutualists on non-native plant establishment and spread, i.e. biological invasions, provides an unexplored analogue to contemporary crop production that accounts for mutualistic services from symbionts like rhizobia and mycorrhizae. The historical exposure of organisms to biotic interactions over evolutionary timescales, or so-called eco-evolutionary experience (EEE), has been used to explain the success of such invasions. In this paper, we stress that consideration of the EEE concept can shed light on how to overcome the loss of microbial mutualist functions following crop domestication and breeding. We propose specific experimental approaches to utilize the wild ancestors of crops to determine whether crop domestication compromised the benefits derived from root microbial symbioses or not. This can predict the potential for success of mutualistic symbiosis manipulation in modern crops and the maintenance of effective microbial mutualisms over the long term.

A Comprehensive, Automatically Updated Fungal ITS Sequence Dataset for Reference-Based Chimera Control in Environmental Sequencing Efforts.

The nuclear ribosomal internal transcribed spacer (ITS) region is the most commonly chosen genetic marker for the molecular identification of fungi in environmental sequencing and molecular ecology studies. Several analytical issues complicate such efforts, one of which is the formation of chimeric-artificially joined-DNA sequences during PCR amplification or sequence assembly. Several software tools are currently available for chimera detection, but rely to various degrees on the presence of a chimera-free reference dataset for optimal performance. However, no such dataset is available for use with the fungal ITS region. This study introduces a comprehensive, automatically updated reference dataset for fungal ITS sequences based on the UNITE database for the molecular identification of fungi. This dataset supports chimera detection throughout the fungal kingdom and for full-length ITS sequences as well as partial (ITS1 or ITS2 only) datasets. The performance of the dataset on a large set of artificial chimeras was above 99.5%, and we subsequently used the dataset to remove nearly 1,000 compromised fungal ITS sequences from public circulation. The dataset is available at http://unite.ut.ee/repository.php and is subject to web-based third-party curation.