Quantifying thermal adaptation of soil microbial respiration.

Quantifying the rate of thermal adaptation of soil microbial respiration is essential in determining potential for carbon cycle feedbacks under a warming climate. Uncertainty surrounding this topic stems in part from persistent methodological issues and difficulties isolating the interacting effects of changes in microbial community responses from changes in soil carbon availability. Here, we constructed a series of temperature response curves of microbial respiration (given unlimited substrate) using soils sampled from around New Zealand, including from a natural geothermal gradient, as a proxy for global warming. We estimated the temperature optima ([Formula: see text]) and inflection point ([Formula: see text]) of each curve and found that adaptation of microbial respiration occurred at a rate of 0.29 °C ± 0.04 1SE for [Formula: see text] and 0.27 °C ± 0.05 1SE for [Formula: see text] per degree of warming. Our results bolster previous findings indicating thermal adaptation is demonstrably offset from warming, and may help quantifying the potential for both limitation and acceleration of soil C losses depending on specific soil temperatures.

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network.

A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities.

Indictors of wetland health improve following small-scale ecological restoration on private land.

Globally wetlands are imperilled and restoring these highly productive and biodiverse ecosystems is key to regaining their lost function and health. Much of the fertile, low-lying land that was historically wetland is now farmed, so privately-owned locations play critical roles in regaining space for wetlands. However, wetland restoration on private property is often small-scale and supported by minimal funding and expertise. Little is known about what these efforts achieve, and what contexts facilitate the greatest gains in wetland health. Using a paired plot design for 18 restored and 18 unrestored wetlands, we aimed to understand changes in wetland health following restoration on private property. We characterised plant and microbial communities and soil characteristics following wetland restoration and explored how environmental settings of restored wetlands related to the clustering of wetland health indicators. We found that all indicators of wetland health significantly increased following restoration except for the ratio of Gram negative to Gram positive bacteria. Restoration enhanced plant alpha and beta diversity, adding ~13 native plant species per plot. Soils in restored wetlands contained 20% more organic matter, and 25% more microbial biomass, which was driven by an increased abundance of fungi. Restoration reduced soil bulk density by 0.19 g-1 cm3 and Olsen Phosphorus by 23%. These effects on soil physical characteristics and microbial communities were strongest in the wettest locations. Restored wetlands clustered into three main groups based on indicators of wetland health. Hydrological flow explained the clustering of wetlands, with riverine wetlands exhibiting greater indicators of recovery than depressional wetlands, suggesting that hydrological flow may influence post-restoration recovery. Overall, this study shows that small-scale wetland restoration on private land improved wetland health, providing evidence that it can be an effective use of marginal agricultural land.

A network perspective for sustainable agroecosystems.

Nature-based management aims to improve sustainable agroecosystem production, but its efficacy has been variable. We argue that nature-based agroecosystem management could be significantly improved by explicitly considering and manipulating the underlying networks of species interactions. A network perspective can link species interactions to ecosystem functioning and stability, identify influential species and interactions, and suggest optimal management approaches. Recent advances in predicting the network roles of species from their functional traits could allow direct manipulation of network architecture through additions or removals of species with targeted traits. Combined with improved understanding of the structure and dynamics of networks across spatial and temporal scales and interaction types, including social-ecological, applying these tools to nature-based management can contribute to sustainable agroecosystems.

The Fatty Acid Methyl Ester (FAME) profile of Phytophthora agathidicida and its potential use as diagnostic tool.

Phytophthora diseases cause devastation to crops and native ecosystems worldwide. In New Zealand, Phytophthora agathidicida is threatening the survival of kauri, an endemic, culturally and ecologically important tree species. The current method for detecting P. agathidicida is a soil bating assay that is time-consuming and requires high levels of expertise to assess, thus limiting the analytical sample throughput. Here, we characterized the fatty acid methyl ester (FAME) profile of P. agathidicida. We also compared it with the FAME profile of P. cinnamomi and assessed the efficacy of FAME analysis as a diagnostic tool for detecting the pathogen in soil samples. In FAME analysis, the total fatty acid content is isolated from a sample and converted to FAMEs for analysis, a process that takes less than a day. Unique fatty acid acyl chains can serve as biomarkers for specific organisms. We detected 12 fatty acids in P. agathidicida, two of which (20:4ω6 and 20:5ω3) show promise as potential Phytophthora specific biomarkers. Collectively, these findings advance our fundamental understanding of P. agathidicida biology and provide a promising technique to increase the rate of sample processing and the speed of pathogen detection for P. agathidicida in soil.

Phospholipid fatty acid (PLFA) analysis as a tool to estimate absolute abundances from compositional 16S rRNA bacterial metabarcoding data.

Microbial biodiversity monitoring through the analysis of DNA extracted from environmental samples is increasingly popular because it is perceived as being rapid, cost-effective, and flexible concerning the sample types studied. DNA can be extracted from diverse media before high-throughput sequencing of the prokaryotic 16S rRNA gene is used to characterize the taxonomic diversity and composition of the sample (known as metabarcoding). While sources of bias in metabarcoding methodologies are widely acknowledged, previous studies have focused mainly on the effects of these biases within a single substrate type, and relatively little is known of how these vary across substrates. We investigated the effect of substrate type (water, microbial mats, lake sediments, stream sediments, soil and a mock microbial community) on the relative performance of DNA metabarcoding in parallel with phospholipid fatty acid (PLFA) analysis. Quantitative estimates of the biomass of different taxonomic groups in samples were made through the analysis of PLFAs, and these were compared to the relative abundances of microbial taxa estimated from metabarcoding. Furthermore, we used the PLFA-based quantitative estimates of the biomass to adjust relative abundances of microbial groups determined by metabarcoding to provide insight into how the biomass of microbial taxa from PLFA analysis can improve understanding of microbial communities from environmental DNA samples. We used two sets of PLFA biomarkers that differed in their number of PLFAs to evaluate how PLFA biomarker selection influences biomass estimates. Metabarcoding and PLFA analysis provided significantly different views of bacterial composition, and these differences varied among substrates. We observed the most notable differences for the Gram-negative bacteria, which were overrepresented by metabarcoding in comparison to PLFA analysis. In contrast, the relative biomass and relative sequence abundances aligned reasonably well for Cyanobacteria across the tested freshwater substrates. Adjusting relative abundances of microbial taxa estimated by metabarcoding with PLFA-based quantification estimates of the microbial biomass led to significant changes in the microbial community compositions in all substrates. We recommend including independent estimates of the biomass of microbial groups to increase comparability among metabarcoding libraries from environmental samples, especially when comparing communities associated with different substrates.

Climate change and invasion may synergistically affect native plant reproduction.

Global change drivers can interact in synergistic ways, yet the interactive effect of global change drivers, such as climatic warming and species invasions, on plant pollination are poorly represented in experimental studies. We paired manipulative experiments to probe two mechanistic pathways through which plant invasion and warming may alter phenology and reproduction of native plant species. In the first, we tested how experimental warming (+1.7°C) modulated flowering phenology and how this affected flowering overlap between a native plant (Dracophyllum subulatum) and an invasive plant (Calluna vulgaris L.). In the second experiment, we explored how variation in the ratio of native to invasive flowers, and the overall quantity of resources in a floral patch, affected the reproduction of the native species. We hypothesized that the flowering overlap of native and invasive plants would be altered by warming, given that invading plants typically exhibit greater phenological plasticity than native plants. Further, we hypothesized that pollination of native plant flowers would decrease in floral patches dominated by invasive plant flowers, but that this effect would depend on total floral density in the patch. As predicted, the invasive plant had a stronger phenological response to experimental warming than the native plant, resulting in increased flowering overlap between the native the invasive plants. There was a four-fold increase in the number of native flowers co-flowering with high densities of invasive flowers suggesting native plant competition for pollinators with invasive plants under a warmed climate. In the second experiment, we found depressed seed masses of the native species in high density floral patches that were dominated by invasive flowers relative to high density floral patches dominated by native flowers. At low floral densities, seed mass of native plants was unaffected by invasion. Together, these results demonstrate that by increasing their phenological overlap, warming may enhance the magnitude of existing competition for pollination exerted by an invasive plant on a native plant, particularly in plant patches with high floral density. Our results illustrate a novel pathway through which global change drivers can operate synergistically to alter an important ecosystem service: pollination.

Long-term warming alters the composition of Arctic soil microbial communities.

Despite the importance of Arctic soils in the global carbon cycle, we know very little of the impacts of warming on the soil microbial communities that drive carbon and nutrient cycling in these ecosystems. Over a 2-year period, we monitored the structure of soil fungal and bacterial communities in organic and mineral soil horizons in plots warmed by greenhouses for 18 years and in control plots. We found that microbial communities were stable over time but strongly structured by warming. Warming led to significant reductions in the evenness of bacterial communities, while the evenness of fungal communities increased significantly. These patterns were strongest in the organic horizon, where temperature change was greatest and were associated with a significant increase in the dominance of the Actinobacteria and significant reductions in the Gemmatimonadaceae and the Proteobacteria. Greater evenness of the fungal community with warming was associated with significant increases in the ectomycorrhizal fungi, Russula spp., Cortinarius spp., and members of the Helotiales suggesting that increased growth of the shrub Betula nana was an important mechanism driving this change. The shifts in soil microbial community structure appear sufficient to account for warming-induced changes in nutrient cycling in Arctic tundra as climate warms.

Below-ground carbon transfer among Betula nana may increase with warming in Arctic tundra.

• Shrubs are expanding in Arctic tundra, but the role of mycorrhizal fungi in this process is unknown. We tested the hypothesis that mycorrhizal networks are involved in interplant carbon (C) transfer within a tundra plant community. • Here, we installed below-ground treatments to control for C transfer pathways and conducted a (13)CO(2)-pulse-chase labelling experiment to examine C transfer among and within plant species. • We showed that mycorrhizal networks exist in tundra, and facilitate below-ground transfer of C among Betula nana individuals, but not between or within the other tundra species examined. Total C transfer among conspecific B. nana pairs was 10.7 ± 2.4% of photosynthesis, with the majority of C transferred through rhizomes or root grafts (5.2 ± 5.3%) and mycorrhizal network pathways (4.1 ± 3.3%) and very little through soil pathways (1.4 ± 0.35%). • Below-ground C transfer was of sufficient magnitude to potentially alter plant interactions in Arctic tundra, increasing the competitive ability and mono-dominance of B. nana. C transfer was significantly positively related to ambient temperatures, suggesting that it may act as a positive feedback to ecosystem change as climate warms.

Molecular diversity of nifH genes from bacteria associated with high arctic dwarf shrubs.

Biological nitrogen fixation is the primary source of new N in terrestrial arctic ecosystems and is fundamental to the long-term productivity of arctic plant communities. Still, relatively little is known about the nitrogen-fixing microbes that inhabit the soils of many dominant vegetation types. Our objective was to determine which diazotrophs are associated with three common, woody, perennial plants in an arctic glacial lowland. Dryas integrifolia, Salix arctica, and Cassiope tetragona plants in soil were collected at Alexandra Fiord, Ellesmere Island, Canada. DNA was extracted from soil and root samples and a 383-bp fragment of the nifH gene amplified by the polymerase chain reaction. Cloned genotypes were screened for similarity by restriction fragment length polymorphism (RFLP) analysis. Nine primary RFLP phylotypes were identified and 42 representative genotypes selected for sequencing. Majority of sequences (33) were type I nitrogenases, whereas the remaining sequences belonged to the divergent, homologous, type IV group. Within the type I nitrogenases, nifH genes from posited members of the Firmicutes were most abundant, and occurred in root and soil samples from all three plant species. nifH genes from posited Pseudomonads were found to be more closely associated with C. tetragona, whereas nifH genes from putative alpha-Proteobacteria were more commonly associated with D. integrifolia and S. arctica. In addition, 12 clones likely representing a unique clade within the type I nitrogenases were identified. To our knowledge, this study is the first to report on the nifH diversity of arctic plant-associated soil microbes.

Impacts of warming and fertilization on nitrogen-fixing microbial communities in the Canadian High Arctic.

The impacts of simulated climate change (warming and fertilization treatments) on diazotroph community structure and activity were investigated at Alexandra Fiord, Ellesmere Island, Canada. Open Top Chambers, which increased growing season temperatures by 1-3 degrees C, were randomly placed in a dwarf-shrub and cushion-plant dominated mesic tundra site in 1995. In 2000 and 2001 20N:20P2O5:20K2O fertilizer was applied at a rate of 5 gm(-2) year(-1). Estimates of nitrogen fixation rates were made in the field by acetylene reduction assays (ARA). Higher rates of N fixation were observed 19-35 days post-fertilization but were otherwise unaffected by treatments. However, moss cover was significantly positively associated with ARA rate. NifH gene variants were amplified from bulk soil DNA and analyzed by terminal restriction fragment length polymorphism analysis. Non-metric multidimensional scaling was used to ordinate treatment plots in nifH genotype space. NifH gene communities were more strongly structured by the warming treatment late in the growing season, suggesting that an annual succession in diazotroph community composition occurs.