The loss of aboveground plant diversity alters belowground ecosystem function; yet, the mechanisms underpinning this relationship and the degree to which plant community structure and climate mediate the effects of plant species loss remain unclear. Here, we explored how plant species loss through experimental removal shaped belowground function in ecosystems characterized by different climatic regimes and edaphic properties. We measured plant community composition as well as potential carbon (C) and nitrogen (N) mineralization and microbial extracellular enzyme activity in soils collected from four unique plant removal experiments located along an elevational gradient in Colorado, USA. We found that, regardless of the identity of the removed species or the climate at each site, plant removal decreased the absolute variation in potential N mineralization rates and marginally reduced the magnitude of N mineralization rates. While plant species removal also marginally reduced C mineralization rates, C mineralization, unlike N mineralization, displayed sensitivity to the climatic and edaphic differences among sites, where C mineralization was greatest at the high elevation site that receives the most precipitation annually and contains the largest soil total C pool. Plant removal had little impact on soil enzyme activity. Removal effects were not contingent on the amount of biomass removed annually, and shifts in mineralization rates occurred despite only marginal shifts in plant community structure following plant species removal. Our results present a surprisingly simple and consistent pattern of belowground response to the loss of dominant plant species across an elevational gradient with different climatic and edaphic properties, suggesting a common response of belowground ecosystem function to plant species loss regardless of which plant species are lost or the broader climatic context.
Imaging spectroscopy provides the opportunity to incorporate leaf and canopy optical data into ecological studies, but the extent to which remote sensing of vegetation can enhance the study of belowground processes is not well understood. In terrestrial systems, aboveground and belowground vegetation quantity and quality are coupled, and both influence belowground microbial processes and nutrient cycling. We hypothesized that ecosystem productivity, and the chemical, structural and phylogenetic‐functional composition of plant communities would be detectable with remote sensing and could be used to predict belowground plant and soil processes in two grassland biodiversity experiments: the BioDIV experiment at Cedar Creek Ecosystem Science Reserve in Minnesota and the Wood River Nature Conservancy experiment in Nebraska. We tested whether aboveground vegetation chemistry and productivity, as detected from airborne sensors, predict soil properties, microbial processes and community composition. Imaging spectroscopy data were used to map aboveground biomass, green vegetation cover, functional traits and phylogenetic‐functional community composition of vegetation. We examined the relationships between the image‐derived variables and soil carbon and nitrogen concentration, microbial community composition, biomass and extracellular enzyme activity, and soil processes, including net nitrogen mineralization. In the BioDIV experiment—which has low overall diversity and productivity despite high variation in each—belowground processes were driven mainly by variation in the amount of organic matter inputs to soils. As a consequence, soil respiration, microbial biomass and enzyme activity, and fungal and bacterial composition and diversity were significantly predicted by remotely sensed vegetation cover and biomass. In contrast, at Wood River—where plant diversity and productivity were consistently higher—belowground processes were driven mainly by variation in the quality of aboveground inputs to soils. Consequently, remotely sensed functional, chemical and phylogenetic composition of vegetation predicted belowground extracellular enzyme activity, microbial biomass, and net nitrogen mineralization rates but aboveground biomass (or cover) did not. The contrasting associations between the quantity (productivity) and quality (composition) of aboveground inputs with belowground soil attributes provide a basis for using imaging spectroscopy to understand belowground processes across productivity gradients in grassland systems. However, a mechanistic understanding of how above and belowground components interact among different ecosystems remains critical to extending these results broadly.
more » « less- NSF-PAR ID:
- 10374778
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Ecological Monographs
- Volume:
- 92
- Issue:
- 1
- ISSN:
- 0012-9615
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Efforts to catalog global biodiversity have often focused on aboveground taxonomic diversity, with limited consideration of belowground communities. However, diversity aboveground may influence the diversity of belowground communities and vice versa. In addition to taxonomic diversity, the structural diversity of plant communities may be related to the diversity of soil bacterial and fungal communities, which drive important ecosystem processes but are difficult to characterize across broad spatial scales. In forests, canopy structural diversity may influence soil microorganisms through its effects on ecosystem productivity and root architecture, and via associations between canopy structure, stand age, and species richness. Given that structural diversity is one of the few types of diversity that can be readily measured remotely (e.g., using light detection and ranging—LiDAR), establishing links between structural and microbial diversity could facilitate the detection of belowground biodiversity hotspots. We investigated the potential for using remotely sensed information about forest structural diversity as a predictor of soil microbial community richness and composition. We calculated LiDAR‐derived metrics of structural diversity as well as a suite of stand and soil properties from 38 forested plots across the central hardwoods region of Indiana, USA, to test whether forest canopy structure is linked with the community richness and diversity of four key soil microbial groups: bacteria, fungi, arbuscular mycorrhizal (AM) fungi, and ectomycorrhizal (EM) fungi. We found that the density of canopy vegetation is positively associated with the taxonomic richness (alpha diversity) of EM fungi, independent of changes in plant taxonomic richness. Further, structural diversity metrics were significantly correlated with the overall community composition of bacteria, EM, and total fungal communities. However, soil properties were the strongest predictors of variation in the taxonomic richness and community composition of microbial communities in comparison with structural diversity and tree species diversity. As remote sensing tools and algorithms are rapidly advancing, these results may have important implications for the use of remote sensing of vegetation structural diversity for management and restoration practices aimed at preserving belowground biodiversity.
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The Monsoon Rainfall Manipulation Experiment (MRME) is to understand changes in ecosystem structure and function of a semiarid grassland caused by increased precipitation variability, which alters the pulses of soil moisture that drive primary productivity, community composition, and ecosystem functioning. The overarching hypothesis being tested is that changes in event size and variability will alter grassland productivity, ecosystem processes, and plant community dynamics. In particular, we predict that many small events will increase soil CO2 effluxes by stimulating microbial processes but not plant growth, whereas a small number of large events will increase aboveground net primary production (ANPP) and soil respiration by providing sufficient deep soil moisture to sustain plant growth for longer periods of time during the summer monsoon. To measure ANPP (i.e., the change in plant biomass, represented by stems, flowers, fruit and foliage, over time), the vegetation variables in this dataset, including species composition and the cover and height of individuals, are sampled twice yearly (spring and fall) at permanent 1m x 1m plots. The data from these plots is used to build regressions correlating biomass and volume via weights of select harvested species obtained in SEV157, "Net Primary Productivity (NPP) Weight Data." This biomass data is included in SEV206, "Seasonal Biomass and Seasonal and Annual NPP for the Monsoon (MRME) Study."more » « less
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Semi‐arid grasslands on the Mongolian Plateau are expected to experience high inputs of anthropogenic reactive nitrogen in this century. It remains unclear, however, how soil organisms and nutrient cycling are directly affected by N enrichment (i.e., without mediation by plant input to soil) vs. indirectly affected via changes in plant‐related inputs to soils resulting from N enrichment. To test the direct and indirect effects of N enrichment on soil organisms (bacteria, fungi and nematodes) and their associated C and N mineralization, in 2010, we designated two subplots (with plants and without plants) in every plot of a six‐level N‐enrichment experiment established in 1999 in a semi‐arid grassland. In 2014, 4 years after subplots with and without plant were established, N enrichment had substantially altered the soil bacterial, fungal and nematode community structures due to declines in biomass or abundance whether plants had been removed or not. N enrichment also reduced the diversity of these groups (except for fungi) and the soil C mineralization rate and induced a hump‐shaped response of soil N mineralization. As expected, plant removal decreased the biomass or abundance of soil organisms and C and N mineralization rates due to declines in soil substrates or food resources. Analyses of plant‐removal‐induced changes (ratios of without‐ to with‐plant subplots) showed that micro‐organisms and C and N mineralization rates were not enhanced as N enrichment increased but that nematodes were enhanced as N enrichment increased, indicating that the effects of plant removal on soil organisms and mineralization depended on trophic level and nutrient status. Surprisingly, there was no statistical interaction between N enrichment and plant removal for most variables, indicating that plant‐related inputs did not qualitatively change the effects of N enrichment on soil organisms or mineralization. Structural equation modelling confirmed that changes in soil communities and mineralization rates were more affected by the direct effects of N enrichment (via soil acidification and increased N availability) than by plant‐related indirect effects. Our results provide insight into how future changes in N deposition and vegetation may modify below‐ground communities and processes in grassland ecosystems.more » « less
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Abstract Background Anthropogenic activities have increased the inputs of atmospheric reactive nitrogen (N) into terrestrial ecosystems, affecting soil carbon stability and microbial communities. Previous studies have primarily examined the effects of nitrogen deposition on microbial taxonomy, enzymatic activities, and functional processes. Here, we examined various functional traits of soil microbial communities and how these traits are interrelated in a Mediterranean-type grassland administrated with 14 years of 7 g m−2year−1of N amendment, based on estimated atmospheric N deposition in areas within California, USA, by the end of the twenty-first century.
Results Soil microbial communities were significantly altered by N deposition. Consistent with higher aboveground plant biomass and litter, fast-growing bacteria, assessed by abundance-weighted average rRNA operon copy number, were favored in N deposited soils. The relative abundances of genes associated with labile carbon (C) degradation (e.g.,
amyA andcda ) were also increased. In contrast, the relative abundances of functional genes associated with the degradation of more recalcitrant C (e.g.,mannanase andchitinase ) were either unchanged or decreased. Compared with the ambient control, N deposition significantly reduced network complexity, such as average degree and connectedness. The network for N deposited samples contained only genes associated with C degradation, suggesting that C degradation genes became more intensely connected under N deposition.Conclusions We propose a conceptual model to summarize the mechanisms of how changes in above- and belowground ecosystems by long-term N deposition collectively lead to more soil C accumulation.
