Predicting Environmental and Ecological Drivers of Human Population Structure

Landscape, climate, and culture can all structure human populations, but few existing methods are designed to simultaneously disentangle among a large number of variables in explaining genetic patterns. We developed a machine learning method for identifying the variables which best explain migration rates, as measured by the coalescent-based program MAPS that uses shared identical by descent tracts to infer spatial migration across a region of interest. We applied our method to 30 human populations in eastern Africa with high-density single nucleotide polymorphism array data. The remarkable diversity of ethnicities, languages, and environments in this region offers a unique opportunity to explore the variables that shape migration and genetic structure. We explored more than 20 spatial variables relating to landscape, climate, and presence of tsetse flies. The full model explained ∼40% of the variance in migration rate over the past 56 generations. Precipitation, minimum temperature of the coldest month, and elevation were the variables with the highest impact. Among the three groups of tsetse flies, the most impactful was fusca which transmits livestock trypanosomiasis. We also tested for adaptation to high elevation among Ethiopian populations. We did not identify well-known genes related to high elevation, but we did find signatures of positive selection related to metabolism and disease. We conclude that the environment has influenced the migration and adaptation of human populations in eastern Africa; the remaining variance in structure is likely due in part to cultural or other factors not captured in our model.

Warming drives a 'hummockification' of microbial communities associated with decomposing mycorrhizal fungal necromass in peatlands

Dead fungal mycelium (necromass) represents a critical component of soil carbon (C) and nutrient cycles. Assessing how the microbial communities associated with decomposing fungal necromass change as global temperatures rise will help in determining how these belowground organic matter inputs contribute to ecosystem responses. In this study, we characterized the structure of bacterial and fungal communities associated with multiple types of decaying mycorrhizal fungal necromass incubated within mesh bags across a 9°C whole ecosystem temperature enhancement in a boreal peatland. We found major taxonomic and functional shifts in the microbial communities present on decaying mycorrhizal fungal necromass in response to warming. These changes were most pronounced in hollow microsites, which showed convergence towards the necromass-associated microbial communities present in unwarmed hummocks. We also observed a high colonization of ericoid mycorrhizal fungal necromass by fungi from the same genera as the necromass. These results indicate that microbial communities associated with mycorrhizal fungal necromass decomposition are likely to change significantly with future climate warming, which may have strong impacts on soil biogeochemical cycles in peatlands. Additionally, the high enrichment of congeneric fungal decomposers on ericoid mycorrhizal necromass may help to explain the increase in ericoid shrub dominance in warming peatlands.

High Genetic Potential for Proteolytic Decomposition in Northern Peatland Ecosystems

Nitrogen (N) is a scarce nutrient commonly limiting primary productivity. Microbial decomposition of complex carbon (C) into small organic molecules (e.g., free amino acids) has been suggested to supplement biologically fixed N in northern peatlands. We evaluated the microbial (fungal, bacterial, and archaeal) genetic potential for organic N depolymerization in peatlands at Marcell Experimental Forest (MEF) in northern Minnesota. We used guided gene assembly to examine the abundance and diversity of protease genes and further compared them to those of N fixation (nifH) genes in shotgun metagenomic data collected across depths and in two distinct peatland environments (bogs and fens). Microbial protease genes greatly outnumbered nifH genes, with the most abundant genes (archaeal M1 and bacterial trypsin [S01]) each containing more sequences than all sequences attributed to nifH Bacterial protease gene assemblies were diverse and abundant across depth profiles, indicating a role for bacteria in releasing free amino acids from peptides through depolymerization of older organic material and contrasting with the paradigm of fungal dominance in depolymerization in forest soils. Although protease gene assemblies for fungi were much less abundant overall than those for bacteria, fungi were prevalent in surface samples and therefore may be vital in degrading large soil polymers from fresh plant inputs during the early stage of depolymerization. In total, we demonstrate that depolymerization enzymes from a diverse suite of microorganisms, including understudied bacterial and archaeal lineages, are prevalent within northern peatlands and likely to influence C and N cycling.IMPORTANCE Nitrogen (N) is a common limitation on primary productivity, and its source remains unresolved in northern peatlands that are vulnerable to environmental change. Decomposition of complex organic matter into free amino acids has been proposed as an important N source, but the genetic potential of microorganisms mediating this process has not been examined. Such information can inform possible responses of northern peatlands to environmental change. We show high genetic potential for microbial production of free amino acids across a range of microbial guilds in northern peatlands. In particular, the abundance and diversity of bacterial genes encoding proteolytic activity suggest a predominant role for bacteria in regulating productivity and contrasts with a paradigm of fungal dominance of organic N decomposition. Our results expand our current understanding of coupled carbon and nitrogen cycles in northern peatlands and indicate that understudied bacterial and archaeal lineages may be central in this ecosystem's response to environmental change.

Simulated projections of boreal forest peatland ecosystem productivity are sensitive to observed seasonality in leaf physiology†

We quantified seasonal CO2 assimilation capacities for seven dominant vascular species in a wet boreal forest peatland then applied data to a land surface model parametrized to the site (ELM-SPRUCE) to test if seasonality in photosynthetic parameters results in differences in simulated plant responses to elevated CO2 and temperature. We collected seasonal leaf-level gas exchange, nutrient content and stand allometric data from the field-layer community (i.e., Maianthemum trifolium (L.) Sloboda), understory shrubs (Rhododendron groenlandicum (Oeder) Kron and Judd, Chamaedaphne calyculata (L.) Moench., Kalmia polifolia Wangenh. and Vaccinium angustifolium Alton.) and overstory trees (Picea mariana (Mill.) B.S.P. and Larix laricina (Du Roi) K. Koch). We found significant interspecific seasonal differences in specific leaf area, nitrogen content (by area; Na) and photosynthetic parameters (i.e., maximum rates of Rubisco carboxylation (Vcmax25°C), electron transport (Jmax25°C) and dark respiration (Rd25°C)), but minimal correlation between foliar Na and Vcmax25°C, Jmax25°C or Rd25°C, which illustrates that nitrogen alone is not a good correlate for physiological processes such as Rubisco activity that can change seasonally in this system. ELM-SPRUCE was sensitive to the introduction of observed interspecific seasonality in Vcmax25°C, Jmax25°C and Rd25°C, leading to simulated enhancement of net primary production (NPP) using seasonally dynamic parameters as compared with use of static parameters. This pattern was particularly pronounced under simulations with higher temperature and elevated CO2, suggesting a key hypothesis to address with future empirical or observational studies as climate changes. Inclusion of species-specific seasonal photosynthetic parameters should improve estimates of boreal ecosystem-level NPP, especially if impacts of seasonal physiological ontogeny can be separated from seasonal thermal acclimation.

Ecological responses to forest age, habitat, and host vary by mycorrhizal type in boreal peatlands

Despite covering vast areas of boreal North America, the ecological factors structuring mycorrhizal fungal communities in peatland forests are relatively poorly understood. To assess how these communities vary by age (younger vs. mature), habitat (fen vs. bog), and host (conifer trees vs. ericaceous shrub), we sampled the roots of two canopy trees (Larix laricina and Picea mariana) and an ericaceous shrub (Ledum groenlandicum) at four sites in northern Minnesota, USA. To characterize the specific influence of host co-occurrence on mycorrhizal fungal community structure, we also conducted a greenhouse bioassay using the same three hosts. Root samples were assessed using Illumina-based high-throughput sequencing (HTS) of the ITS1 rRNA gene region. As expected, we found that the relative abundance of ectomycorrhizal fungi was high on both Larix and Picea, whereas ericoid mycorrhizal fungi had high relative abundance only on Ledum. Ericoid mycorrhizal fungal richness was significantly higher in mature forests, in bogs, and on Ledum hosts, while ectomycorrhizal fungal richness did not differ significantly across any of these three variables. In terms of community composition, ericoid mycorrhizal fungi were more strongly influenced by host while ectomycorrhizal fungi were more influenced by habitat. In the greenhouse bioassay, the presence of Ledum had consistently stronger effects on the composition of ectomycorrhizal, ericoid, and ericoid-ectomycorrhizal fungal communities than either Larix or Picea. Collectively, these results suggest that partitioning HTS-based datasets by mycorrhizal type in boreal peatland forests is important, as their responses to rapidly changing environmental conditions are not likely to be uniform.