A general stochastic model shows that plant-soil feedbacks can buffer plant species from extinction risks in unpredictable environments

Theory and experiments have demonstrated that negative plant-soil feedback (PSF) promotes coexistence between plant species. Plants and soils, however, face the challenge of an increasingly unpredictable environment due to multiple global change factors. Environmental stochasticity induces fluctuations that increase the variability and unpredictability of population dynamics, plant associations in the community and thus properties such as overall productivity. In this paper, we formulate a stochastic version of a classic PSF deterministic model, which describes the outcome of plant species competition in the presence of soil feedback. Especially when the soil feedback is negative, the deterministic expectation is that pulse perturbations to the system (e.g. a drought episode) cause plants and soil to move away from their equilibrium and then return to it. Environmental stochasticity alters this expectation: the system can either settle into a fluctuation regime around the deterministic expectation, or plant species may go extinct. Probability of extinction predictably increases with environmental stochasticity but the more negative the PSF, the more it can counteract the increase in extinction probability caused by increased environmental stochasticity. We stress that in nature the actual impact of PSF will depend on the interactions that link different types of soil organisms to plant species. We conclude that theory shows that plant communities with strong negative PSF are best placed to withstand the risk posed by increased environmental stochasticity but also that we still need more experimental evidence to validate theory and develop applications

Eating from the same plate? Revisiting the role of labile carbon inputs in the soil food web

AbstractAn increasing number of empirical studies are challenging the central fundamentals on which the classical soil food web model is built. This model assumes that bacteria consume labile substrates twice as fast as fungi, and that mycorrhizal fungi do not decompose organic matter. Here, we build on emerging evidence that points to significant consumption of labile C by fungi, and to the ability of ectomycorrhizal fungi to decompose organic matter, to show that labile C constitutes a major and presently underrated source of C for the soil food web. We use a simple model describing the dynamics of a recalcitrant and a labile C pool and their consumption by fungi and bacteria to show that fungal and bacterial populations can coexist in a stable state with large inputs into the labile C pool and a high fungal use of labile C. We propose a new conceptual model for the bottom trophic level of the soil food web, with organic C consisting of a continuous pool rather than two or three distinct pools, and saprotrophic fungi using substantial amounts of labile C. Incorporation of these concepts will increase our understanding of soil food web dynamics and functioning under changing conditions

Fluctuating ecological networks: A synthesis of maximum-entropy approaches for pattern detection and process inference

1. Ecological networks such as plant–pollinator systems and food webs vary in space and time. This variability includes fluctuations in global properties such as the total number and intensity of interactions in the network but also in the number and intensity of local (i.e. node level) species interactions. 2. Fluctuations of species' properties can significantly affect higher-order network features, for example, robustness and nestedness, and should therefore be taken into account in null models for pattern detection and hypothesis testing. 3. In ecological research, classical null models treat node-level properties as ‘hard’ constraints that cannot fluctuate. Here, we review and synthesize a set of maximum-entropy methods that allow for fluctuating (‘soft’) constraints, offering a new addition to the classical toolkit of the ecologist. We illustrate the methods with some practical examples, pointing to currently available open-source computer codes. We clarify how this approach can be used by experimental ecologists to detect non-random patterns with null models that not only rewire, but also redistribute interaction strengths by allowing fluctuations in the enforced constraints. 4. Explicit modelling of interspecific heterogeneity through local (i.e. species level) fluctuations of topological and quantitative constraints offers a statistically robust and expanded (e.g. including weighted links) set of tools to understand the assembly and resilience of ecological networks

Indigenous Arbuscular Mycorrhizal Fungal Assemblages Protect Grassland Host Plants from Pathogens

Plant roots can establish associations with neutral, beneficial and pathogenic groups of soil organisms. Although it has been recognized from the study of individual isolates that these associations are individually important for plant growth, little is known about interactions of whole assemblages of beneficial and pathogenic microorganisms associating with plants

Scavenging beetles control the temporal response of soil communities to carrion decomposition

1. Carrion is a frequent but overlooked source of nutrients to the soil. The decomposition of carrion is accelerated by invertebrate scavengers but the impact of the scavengers on below-ground biota and its functions is scarcely known. 2. We conducted a laboratory experiment to investigate the effects of the burying beetle Nicrophorus vespilloides on the soil community of a temperate broadleaved forest. We assembled microcosms from soil collected from an oak woodland and treated them with mouse (Mus musculus) carcasses and mating pairs of burying beetles (♀+♂) in a factorial design with control soils. We sampled independent replicates over time to investigate how the beetles affect soil microarthropods and microbial biomass (bacteria and fungi) in relation to soil pH and organic matter content. 3. The beetle treatment initially reduced total microbial biomass and abundance of major groups of microarthropods relative to the control soil. At the same time, organic matter increased in the beetle treatment and then dropped to the pre-beetle level (i.e. soil baseline) at the end of the beetle breeding cycle (2 weeks). The rapid temporal changes in organic matter were mimicked by the relative abundances of the dominant microarthropod groups, with Oribatida relatively more abundant than Collembola and predaceous mites in the beetle treatment. The overall final effect of the beetle (relative to the laboratory control) on microarthropods was negative but the beetle kept these variables within the levels observed for freshly collected soil (baseline), while the final effect on pH was positive, and most likely driven by the surplus of nutrients from the carcass and biochemical changes triggered by the decomposition process. 4. In nature, scavenging invertebrates are widespread. Our study demonstrates that beetles breeding in carcasses regulate the dynamics of key components of the soil food web, including microbial biomass, changes in the relative abundances of dominant microarthropods, and soil organic matter and pH. Given the abundance of these beetles in nature, the study implies that the distribution of these beetles is a key driver of variation in soil nutrient cycling in woodlands

Soil microbes and community coalescence

Community coalescence is a recently introduced term describing the interaction of entire communities and their environments. We here explicitly place the concept of community coalescence in a soil microbial context, exploring intrinsic and extrinsic drivers of such coalescence events. Examples of intrinsic events include the action of earthworms and the dynamics of soil aggregates, while extrinsic events are exemplified by tillage, flooding, litterfall, outplanting, and the addition of materials containing microbial communities. Aspects of global change may alter the frequency or severity of coalescence events. We highlight functional consequences of community coalescence in soil, and suggest ways to experimentally tackle this phenomenon. Soil ecology as a whole stands to benefit from conceptualizing soil biodiversity in terms of dynamic coalescent microbial assemblages

Intensive grassland management disrupts below-ground multi-trophic resource transfer in response to drought

Modification of soil food webs by land management may alter the response of ecosystem processes to climate extremes, but empirical support is limited and the mechanisms involved remain unclear. Here we quantify how grassland management modifies the transfer of recent photosynthates and soil nitrogen through plants and soil food webs during a post-drought period in a controlled field experiment, using in situ 13C and 15N pulse-labelling in intensively and extensively managed fields. We show that intensive management decrease plant carbon (C) capture and its transfer through components of food webs and soil respiration compared to extensive management. We observe a legacy effect of drought on C transfer pathways mainly in intensively managed grasslands, by increasing plant C assimilation and 13C released as soil CO2 efflux but decreasing its transfer to roots, bacteria and Collembola. Our work provides insight into the interactive effects of grassland management and drought on C transfer pathways, and highlights that capture and rapid transfer of photosynthates through multi-trophic networks are key for maintaining grassland resistance to drought

insights for ecological applications from the German Biodiversity Exploratories

Biodiversity, a multidimensional property of natural systems, is difficult to quantify partly because of the multitude of indices proposed for this purpose. Indices aim to describe general properties of communities that allow us to compare different regions, taxa, and trophic levels. Therefore, they are of fundamental importance for environmental monitoring and conservation, although there is no consensus about which indices are more appropriate and informative. We tested several common diversity indices in a range of simple to complex statistical analyses in order to determine whether some were better suited for certain analyses than others. We used data collected around the focal plant Plantago lanceolata on 60 temperate grassland plots embedded in an agricultural landscape to explore relationships between the common diversity indices of species richness (S), Shannon's diversity (H'), Simpson's diversity (D1), Simpson's dominance (D2), Simpson's evenness (E), and Berger–Parker dominance (BP). We calculated each of these indices for herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and P. lanceolata molecular and chemical diversity. Including these trait-based measures of diversity allowed us to test whether or not they behaved similarly to the better studied species diversity. We used path analysis to determine whether compound indices detected more relationships between diversities of different organisms and traits than more basic indices. In the path models, more paths were significant when using H', even though all models except that with E were equally reliable. This demonstrates that while common diversity indices may appear interchangeable in simple analyses, when considering complex interactions, the choice of index can profoundly alter the interpretation of results. Data mining in order to identify the index producing the most significant results should be avoided, but simultaneously considering analyses using multiple indices can provide greater insight into the interactions in a system