Contrasting mycorrhizal functionality in abiotic stress tolerance of woody species

Current understanding of how woody plants respond to abiotic stress and how mycorrhizal interactions mitigate this stress is limited, as research has mostly focused on single stress factors. The diverse range of woody plants and mycorrhizal fungi, and the varying intensity and composition of multiple stress factors in different regions worldwide, have made it difficult to study these highly functional symbiotic interactions from a global perspective. Here, we used a top-down approach that involved partitioning known interactions into functional types, and mapping stress tolerances and interactions into overlapping heatmaps. We used a comprehensive dataset of 621 woody species' tolerance of shade, drought, waterlogging, and cold stress, as well as their mycorrhizal interaction data, to test how stress polytolerance correlates with different functional types of mycorrhiza. We show that single mycorrhizal type associates with shade tolerance, while dual type with cold and waterlogging tolerance. Both arbuscular mycorrhiza and obligate interactions are more abundant in drought stress tolerance conditions, while ectomycorrhiza and facultative interactions are found in more cold and waterlogged stressful conditions. Thus, functionally distinct mycorrhizal interactions form significantly contrasting stress mitigation patterns with woody species, providing insights into both evolutionary and biogeographic patterns related to the development of plant-mycorrhiza interactions.

Diversity across organisational scale emerges through dispersal ability and speciation dynamics in tropical fish

BACKGROUND

Biodiversity exists at different levels of organisation: e.g. genetic, individual, population, species, and community. These levels of organisation all exist within the same system, with diversity patterns emerging across organisational scales through several key processes. Despite this inherent interconnectivity, observational studies reveal that diversity patterns across levels are not consistent and the underlying mechanisms for variable continuity in diversity across levels remain elusive. To investigate these mechanisms, we apply a spatially explicit simulation model to simulate the global diversification of tropical reef fishes at both the population and species levels through emergent population-level processes.

RESULTS

We find significant relationships between the population and species levels of diversity which vary depending on both the measure of diversity and the spatial partitioning considered. In turn, these population-species relationships are driven by modelled biological trait parameters, especially the divergence threshold at which populations speciate.

CONCLUSIONS

To explain variation in multi-level diversity patterns, we propose a simple, yet novel, population-to-species diversity partitioning mechanism through speciation which disrupts continuous diversity patterns across organisational levels. We expect that in real-world systems this mechanism is driven by the molecular dynamics that determine genetic incompatibility, and therefore reproductive isolation between individuals. We put forward a framework in which the mechanisms underlying patterns of diversity across organisational levels are universal, and through this show how variable patterns of diversity can emerge through organisational scale.

Detecting steps in spatial genetic data: Which diversity measures are best?

Accurately detecting sudden changes, or steps, in genetic diversity across landscapes is important for locating barriers to gene flow, identifying selectively important loci, and defining management units. However, there are many metrics that researchers could use to detect steps and little information on which might be the most robust. Our study aimed to determine the best measure/s for genetic step detection along linear gradients using biallelic single nucleotide polymorphism (SNP) data. We tested the ability to differentiate between linear and step-like gradients in genetic diversity, using a range of diversity measures derived from the q-profile, including allelic richness, Shannon Information, GST, and Jost-D, as well as Bray-Curtis dissimilarity. To determine the properties of each measure, we repeated simulations of different intensities of step and allele proportion ranges, with varying genome sample size, number of loci, and number of localities. We found that alpha diversity (within-locality) based measures were ineffective at detecting steps. Further, allelic richness-based beta (between-locality) measures (e.g., Jaccard and Sørensen dissimilarity) were not reliable for detecting steps, but instead detected departures from fixation. The beta diversity measures best able to detect steps were: Shannon Information based measures, GST based measures, a Jost-D related measure, and Bray-Curtis dissimilarity. No one measure was best overall, with a trade-off between those measures with high step detection sensitivity (GST and Bray-Curtis) and those that minimised false positives (a variant of Shannon Information). Therefore, when detecting steps, we recommend understanding the differences between measures and using a combination of approaches.