Allelopathic effects of native and invasive Brassica nigra do not support the novel-weapons hypothesis.

PREMISE: The novel-weapons hypothesis predicts that some plants are successful invaders because they release allelopathic compounds that are highly suppressive to naïve competitors in invaded ranges but are relatively ineffective against competitors in the native range. For its part, the evolution of enhanced weaponry hypothesis predicts that invasive populations may evolve increased expression of the allelopathic compounds. However, these predictions have rarely been tested empirically. METHODS: Here, we made aqueous extracts of roots and shoots of invasive (North American) and native (European) Brassica nigra plants. Seeds of nine species from North America and nine species from Europe were exposed to these extracts. As control solutions, we used pure distilled water and distilled water with the osmotic potential adjusted with polyethylene glycol (PEG) to match that of root and shoot extracts of B. nigra. RESULTS: The extracts had a strong negative effect on germination rates and seedling root lengths of target species compared to the water-control. Compared to the osmolality-adjusted controls, the extracts had a negative effect on seedling root length. We found no differences between the effects of B. nigra plant extracts from the invasive vs. native populations on germination rates and seedling root growth of target plant species. Responses were largely independent of whether the target plant species were from the invaded or native range of B. nigra. CONCLUSIONS: The results show that B. nigra can interfere with other species through allelochemical interactions, but do not support predictions of the novel-weapons hypothesis and evolution of increased allelopathy.

Global Microbiome Diversity Scaling in Hot Springs With DAR (Diversity-Area Relationship) Profiles.

The spatial distribution of biodiversity (i.e., the biogeography) of the hot-spring microbiome is critical for understanding the microbial ecosystems in hot springs. We investigated the microbiome diversity scaling (changes) over space by analyzing the diversity-area relationship (DAR), which is an extension to classic SAR (species-area relationship) law in biogeography. We built DAR models for archaea and bacteria with 16S-rRNA sequencing datasets from 165 hot springs globally. From the DAR models, we sketch out the biogeographic maps of hot-spring microbiomes by constructing: (i) DAR profile-measuring the archaea or bacteria diversity scaling over space (areas); (ii) PDO (pair-wise diversity overlap or similarity) profile-estimating the PDO between two hot springs; (iii) MAD (maximal accrual diversity) profile-predicting the global MAD; (iv) LRD/LGD (ratio of local diversity to regional or global diversity) profile. We further investigated the differences between archaea and bacteria in their biogeographic maps. For example, the comparison of DAR-profile maps revealed that the archaea diversity is more heterogeneous (i.e., more diverse) or scaling faster than the bacterial diversity does in terms of species numbers (species richness), but is less heterogeneous (i.e., less diverse) or scaling slower than bacteria when the diversity (Hill numbers) were weighted in favor of more abundant dominant species. When the diversity is weighted equally in terms of species abundances, archaea, and bacteria are equally heterogeneous over space or scaling at the same rate. Finally, unified DAR models (maps) were built with the combined datasets of archaea and bacteria.