Search for: All records

Abstract The spatial heterogeneity of soil’s microhabitats warrants the study of ecological patterns and community assembly processes in the context of physical disturbance that disrupts the inherent spatial isolation of soil microhabitats and microbial communities. By mixing soil at various frequencies in a 16-week lab incubation, we explored the effects of physical disturbance on soil bacterial richness, community composition, and community assembly processes. We hypothesized that well-mixed soil would harbor a less rich microbial community, with community assembly marked by homogenizing dispersal and homogeneous selection. Using 16S rRNA gene sequencing, we inferred community assembly processes, estimated richness and differential abundance, and calculated compositional dissimilarity. Findings supported our hypotheses, with > 20% decrease in soil bacterial richness in well-mixed soil. Soil mixing caused communities to diverge from unmixed controls (Bray–Curtis dissimilarity; 0.75 vs. 0.25), while reducing within-group heterogeneity. Our results imply that the vast diversity observed in soil may be supported by spatial heterogeneity and isolation of microbial communities, and also provide insight into the effects of physical disturbance and community coalescence events. By isolating and better understanding the effects of spatial heterogeneity and disconnectivity on soil microbial communities, we can better extrapolate how anthropogenic disturbances may affect broad soil functions. 

Metagenomes encode an enormous diversity of proteins, reflecting a multiplicity of functions and activities. Exploration of this vast sequence space has been limited to a comparative analysis against reference microbial genomes and protein families derived from those genomes. Here, to examine the scale of yet untapped functional diversity beyond what is currently possible through the lens of reference genomes, we develop a computational approach to generate reference-free protein families from the sequence space in metagenomes. We analyze 26,931 metagenomes and identify 1.17 billion protein sequences longer than 35 amino acids with no similarity to any sequences from 102,491 reference genomes or the Pfam database. Using massively parallel graph-based clustering, we group these proteins into 106,198 novel sequence clusters with more than 100 members, doubling the number of protein families obtained from the reference genomes clustered using the same approach. We annotate these families on the basis of their taxonomic, habitat, geographical, and gene neighborhood distributions and, where sufficient sequence diversity is available, predict protein three-dimensional models, revealing novel structures. Overall, our results uncover an enormously diverse functional space, highlighting the importance of further exploring the microbial functional dark matter. 

Abstract Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the “firehose” of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways towards mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.