Biodiversity mediates the effects of stressors but not nutrients on litter decomposition

Global changes and their environmental stressors have a significant impact on soil biodiversity-A meta-analysis

Identifying the main threats to soil biodiversity is crucial as soils harbor ∼60% of global biodiversity. Many previous meta-analyses investigating the impact of different global changes (GCs) on biodiversity have omitted soil fauna or are limited by the GCs studied. We conducted a broad-scale meta-analysis focused on soil fauna communities, analyzing 3,161 effect sizes from 624 publications studying climate change, land-use intensification, pollution, nutrient enrichment, invasive species and habitat fragmentation. Land-use intensification resulted in large reductions in soil fauna communities, especially for the larger-bodied groups. Unexpectedly, pollution caused the largest negative impact on soil biodiversity - particularly worrying due to continually increasing levels of pollution and poor mechanistic understanding of impacts relative to other GCs. Not all GCs and stressors were detrimental; organic-based nutrient enrichment often resulted in positive responses. Including soil biodiversity in large-scale analyses is vital to fully understand the impact of GCs across the different realms.

Environmental heterogeneity at two spatial scales affects litter diversity-decomposition relationships

The effects of biodiversity on ecological processes have been experimentally evaluated mainly at the local scale under homogeneous conditions. To scale up experimentally based biodiversity-functioning relationships, there is an urgent need to understand how such relationships are affected by the environmental heterogeneity that characterizes larger spatial scales. Here, we tested the effects of an 800-m elevation gradient (a large-scale environmental factor) and forest habitat (a fine-scale factor) on litter diversity-decomposition relationships. To better understand local and landscape scale mechanisms, we partitioned net biodiversity effects into complementarity, selection, and insurance effects as applicable at each scale. We assembled different litter mixtures in aquatic microcosms that simulated natural tree holes, replicating mixtures across blocks nested within forest habitats (edge, interior) and elevations (low, mid, high). We found that net biodiversity and complementarity effects increased over the elevation gradient, with their strength modified by forest habitat and the identity of litter in mixtures. Complementarity effects at local and landscape scales were greatest for combinations of nutrient-rich and nutrient-poor litters, consistent with nutrient transfer mechanisms. By contrast, selection effects were consistently weak and negative at both scales. Selection effects at the landscape level were due mainly to nonrandom overyielding rather than spatial insurance effects. Our findings demonstrate that the mechanisms by which litter diversity affects decomposition are sensitive to environmental heterogeneity at multiple scales. This has implications for the scaling of biodiversity-ecosystem function relationships and suggests that future shifts in environmental conditions due to climate change or land use may impact the functioning of aquatic ecosystems.

Hill-Chao numbers allow decomposing gamma multifunctionality into alpha and beta components

Biodiversity-ecosystem functioning (BEF) research has provided strong evidence and mechanistic underpinnings to support positive effects of biodiversity on ecosystem functioning, from single to multiple functions. This research has provided knowledge gained mainly at the local alpha scale (i.e. within ecosystems), but the increasing homogenization of landscapes in the Anthropocene has raised the potential that declining biodiversity at the beta (across ecosystems) and gamma scales is likely to also impact ecosystem functioning. Drawing on biodiversity theory, we propose a new statistical framework based on Hill-Chao numbers. The framework allows decomposition of multifunctionality at gamma scales into alpha and beta components, a critical but hitherto missing tool in BEF research; it also allows weighting of individual ecosystem functions. Through the proposed decomposition, new BEF results for beta and gamma scales are discovered. Our novel approach is applicable across ecosystems and connects local- and landscape-scale BEF assessments from experiments to natural settings.

Drivers of soil microbial and detritivore activity across global grasslands

Covering approximately 40% of land surfaces, grasslands provide critical ecosystem services that rely on soil organisms. However, the global determinants of soil biodiversity and functioning remain underexplored. In this study, we investigate the drivers of soil microbial and detritivore activity in grasslands across a wide range of climatic conditions on five continents. We apply standardized treatments of nutrient addition and herbivore reduction, allowing us to disentangle the regional and local drivers of soil organism activity. We use structural equation modeling to assess the direct and indirect effects of local and regional drivers on soil biological activities. Microbial and detritivore activities are positively correlated across global grasslands. These correlations are shaped more by global climatic factors than by local treatments, with annual precipitation and soil water content explaining the majority of the variation. Nutrient addition tends to reduce microbial activity by enhancing plant growth, while herbivore reduction typically increases microbial and detritivore activity through increased soil moisture. Our findings emphasize soil moisture as a key driver of soil biological activity, highlighting the potential impacts of climate change, altered grazing pressure, and eutrophication on nutrient cycling and decomposition within grassland ecosystems.

Enhancing the structural diversity between forest patches-A concept and real-world experiment to study biodiversity, multifunctionality and forest resilience across spatial scales

Intensification of land use by humans has led to a homogenization of landscapes and decreasing resilience of ecosystems globally due to a loss of biodiversity, including the majority of forests. Biodiversity-ecosystem functioning (BEF) research has provided compelling evidence for a positive effect of biodiversity on ecosystem functions and services at the local (α-diversity) scale, but we largely lack empirical evidence on how the loss of between-patch β-diversity affects biodiversity and multifunctionality at the landscape scale (γ-diversity). Here, we present a novel concept and experimental framework for elucidating BEF patterns at α-, β-, and γ-scales in real landscapes at a forest management-relevant scale. We examine this framework using 22 temperate broadleaf production forests, dominated by Fagus sylvatica. In 11 of these forests, we manipulated the structure between forest patches by increasing variation in canopy cover and deadwood. We hypothesized that an increase in landscape heterogeneity would enhance the β-diversity of different trophic levels, as well as the β-functionality of various ecosystem functions. We will develop a new statistical framework for BEF studies extending across scales and incorporating biodiversity measures from taxonomic to functional to phylogenetic diversity using Hill numbers. We will further expand the Hill number concept to multifunctionality allowing the decomposition of γ-multifunctionality into α- and β-components. Combining this analytic framework with our experimental data will allow us to test how an increase in between patch heterogeneity affects biodiversity and multifunctionality across spatial scales and trophic levels to help inform and improve forest resilience under climate change. Such an integrative concept for biodiversity and functionality, including spatial scales and multiple aspects of diversity and multifunctionality as well as physical and environmental structure in forests, will go far beyond the current widely applied approach in forestry to increase resilience of future forests through the manipulation of tree species composition.

Interactive effects of global change drivers as determinants of the link between soil biodiversity and ecosystem functioning

Biodiversity, both aboveground and belowground, is negatively affected by global changes such as drought or warming. This loss of biodiversity impacts Earth's ecosystems, as there is a positive relationship between biodiversity and ecosystem functioning (BEF). Even though soils host a large fraction of biodiversity that underlies major ecosystem functions, studies exploring the relationship between soil biodiversity and ecosystem functioning (sBEF) as influenced by global change drivers (GCDs) remain scarce. Here we highlight the need to decipher sBEF relationships under the effect of interactive GCDs that are intimately connected in a changing world. We first state that sBEF relationships depend on the type of function (e.g., C cycling or decomposition) and biodiversity facet (e.g., abundance, species richness, or biomass) considered. Then, we shed light on the impact of single and interactive GCDs on soil biodiversity and sBEF and show that results from scarce studies studying interactive effects range from antagonistic to additive to synergistic when two individual GCDs cooccur. This indicates the need for studies quantitatively accounting for the impacts of interactive GCDs on sBEF relationships. Finally, we provide guidelines for optimized methodological and experimental approaches to study sBEF in a changing world that will provide more valuable information on the real impact of (interactive) GCDs on sBEF. Together, we highlight the need to decipher the sBEF relationship in soils to better understand soil functioning under ongoing global changes, as changes in sBEF are of immediate importance for ecosystem functioning.

Mixed-litter effects of fresh leaf semi-decomposed litter and fine root on soil enzyme activity and microbial community in an evergreen broadleaf karst forest in southwest China

Litter decomposition is the main process that affects nutrient cycling and carbon budgets in mixed forests. However, knowledge of the response of the soil microbial processes to the mixed-litter decomposition of fresh leaf, semi-decomposed leaf and fine root is limited. Thus, a laboratory microcosm experiment was performed to explore the mixed-litter effects of fresh leaf, semi-decomposed leaf and fine root on the soil enzyme activity and microbial community in an evergreen broadleaf karst forest in Southwest China. Fresh leaf litter, semi-decomposed litter and fine root in the Parakmeria nitida and Dayaoshania cotinifolia forests, which are unique protective species and dominant species in the evergreen broadleaf forest, were decomposed alone and in all possible combinations, respectively. Our results showed that the mass loss of fresh leaf litter in three mixed-litter treatment was significantly higher than that in two mixed-litter treatment in the P. nitida and D. cotinifolia forests. Mass loss of fine root in the single litter treatment was significantly lower in the P. nitida forest and higher in the D. cotinifolia forest compared to that in the other litter treatments. There were insignificant differences in the activities of β-glucosidase (BG) and leucine aminopeptidase (LAP) between control and mixed-litter treatment in the P. nitida forest and between control and single litter treatment in the D. cotinifolia forest. The N-acetyl-β-D-glucosaminidase (NAG) activity was significantly increased by the single litter decomposition of fresh leaf and fine root and three mixed-litter decomposition in the P. nitida and D. cotinifolia forests. The activity of acid phospomonoesterase (AP) in the decomposition of fresh leaf litter was lower in the P. nitida forest and higher in the D. cotinifolia forest compared to that in control. The most dominant soil bacteria were Proteobacteria in the P. nitida forest and were Actinobacteria and Proteobacteria in the D. cotinifolia forest. Shannon, Chao1, ACE and PD indexes in the mixed-litter decomposition of fresh leaf and semi-decomposition litter were higher than that in control in P. nitida forest. There were insignificant differences in observed species and indexes of Chao1, ACE and PD between litter treatments in the D. cotinifolia forest. Richness of mixed-litter significantly affected mass loss, soil enzyme activity and microbial diversity in the P. nitida forest. Litter N concentration and the presence of fresh leaf litter were significantly correlated with the mass loss and soil enzyme activity in the P. nitida and D. cotinifolia forests. These results indicated that the presence of fresh leaf litter showed a non-negligible influence on mixed-litter decomposition and soil enzyme activity, which might be partly explained by litter initial quality in the P. nitida and D. cotinifolia forests.

Are experiment sample sizes adequate to detect biologically important interactions between multiple stressors?

As most ecosystems are being challenged by multiple, co-occurring stressors, an important challenge is to understand and predict how stressors interact to affect biological responses. A popular approach is to design factorial experiments that measure biological responses to pairs of stressors and compare the observed response to a null model expectation. Unfortunately, we believe experiment sample sizes are inadequate to detect most non-null stressor interaction responses, greatly hindering progress. Using both real and simulated data, we show sample sizes typical of many experiments (<6) can (i) only detect very large deviations from the additive null model, implying many important non-null stressor-pair interactions are being missed, and (ii) potentially lead to mostly statistical outliers being reported. Computer code that simulates data under either additive or multiplicative null models is provided to estimate statistical power for user-defined responses and sample sizes, and we recommend this is used to aid experimental design and interpretation of results. We suspect that most experiments may require 20 or more replicates per treatment to have adequate power to detect nonadditive. However, estimates of power need to be made while considering the smallest interaction of interest, i.e., the lower limit for a biologically important interaction, which is likely to be system-specific, meaning a general guide is unavailable. We discuss ways in which the smallest interaction of interest can be chosen, and how sample sizes can be increased. Our main analyses relate to the additive null model, but we show similar problems occur for the multiplicative null model, and we encourage similar investigations into the statistical power of other null models and inference methods. Without knowledge of the detection abilities of the statistical tools at hand or the definition of the smallest meaningful interaction, we will undoubtedly continue to miss important ecosystem stressor interactions.

Are experiment sample sizes adequate to detect biologically important interactions between multiple stressors?

As most ecosystems are being challenged by multiple, co-occurring stressors, an important challenge is to understand and predict how stressors interact to affect biological responses. A popular approach is to design factorial experiments that measure biological responses to pairs of stressors and compare the observed response to a null model expectation. Unfortunately, we believe experiment sample sizes are inadequate to detect most non-null stressor interaction responses, greatly hindering progress. Using both real and simulated data, we show sample sizes typical of many experiments (<6) can (i) only detect very large deviations from the additive null model, implying many important non-null stressor-pair interactions are being missed, and (ii) potentially lead to mostly statistical outliers being reported. Computer code that simulates data under either additive or multiplicative null models is provided to estimate statistical power for user-defined responses and sample sizes, and we recommend this is used to aid experimental design and interpretation of results. We suspect that most experiments may require 20 or more replicates per treatment to have adequate power to detect nonadditive. However, estimates of power need to be made while considering the smallest interaction of interest, i.e., the lower limit for a biologically important interaction, which is likely to be system-specific, meaning a general guide is unavailable. We discuss ways in which the smallest interaction of interest can be chosen, and how sample sizes can be increased. Our main analyses relate to the additive null model, but we show similar problems occur for the multiplicative null model, and we encourage similar investigations into the statistical power of other null models and inference methods. Without knowledge of the detection abilities of the statistical tools at hand or the definition of the smallest meaningful interaction, we will undoubtedly continue to miss important ecosystem stressor interactions.

Linking pollution to biodiversity and ecosystem multifunctionality across benthic-pelagic habitats of a large eutrophic lake: A whole-ecosystem perspective

Biodiversity loss is often an important driver of the deterioration of ecosystem functioning in freshwater ecosystems. However, it is far from clear how multiple ecosystem functions (i.e., ecosystem multifunctionality, EMF) relate to biodiversity across the benthic-pelagic habitats of entire ecosystems or how environmental stress such as eutrophication and heavy metals enrichment might regulate the biodiversity-EMF relationships. Here, we explored the biodiversity and EMF across benthic-pelagic habitats of the large eutrophic Lake Taihu in China, and further examined abiotic factors underlying the spatial variations in EMF and its relationships with biodiversity. In our results, EMF consistently showed positive relationships to the biodiversity of multiple taxonomic groups, such as benthic bacteria, bacterioplankton and phytoplankton. Both sediment heavy metals and total phosphorus significantly explained the spatial variations in the EMF, whereas the former were more important than the latter. Further, sediment heavy metals mediated EMF through the diversity of benthic bacteria and bacterioplankton, while nutrients such as phosphorus in both the sediments and overlaying water altered EMF via phytoplankton diversity. This indicates the importance of pollution in regulating the relationships between biodiversity and EMF in freshwater environments. Our findings provide evidence that freshwater biodiversity loss among phytoplankton and bacteria will likely weaken ecosystem functioning. Our results further suggest that abiotic factors such as heavy metals, beyond nutrient enrichment, may provide relatively earlier signals of impaired ecosystem functioning during eutrophication process.

Fungal Biodiversity Mediates the Effects of Drying on Freshwater Ecosystem Functioning

Investigating the influence of biodiversity on ecosystem functioning over environmental gradients is needed to anticipate ecosystem responses to global change. However, our understanding of the functional role of freshwater biodiversity, especially for microbes, is mainly based on manipulative experiments, where biodiversity and environmental variability are minimized. Here, we combined observational and manipulative experiments to analyse how fungal biodiversity responds to and mediates the impacts of drying on two key ecosystem processes: organic matter decomposition and fungal biomass accrual. Our observational data set consists of fungal biodiversity and ecosystem processes from 15 streams spanning a natural gradient of flow intermittence. Our manipulative design evaluates the responses of ecosystem processes to two fungal richness levels crossed with three levels of drying. For the observational experiment, we found that increasing the duration of drying reduced fungal species richness and caused compositional changes. Changes in species composition were driven by species turnover, suggesting resistance mechanisms to cope with drying. We also found that fungal richness had a positive effect on organic matter decomposition and fungal biomass accrual. Positive effects of fungal biodiversity were consistent when controlling for the effects of drying duration on richness by means of structural equation modelling. In addition, our results for the manipulative experiment showed that the positive effects of higher richness on both ecosystem processes were evident even when exposed to short or long simulated drying. Overall, our study suggests that maintaining high levels of biodiversity is crucial for maintaining functional freshwater ecosystems in response to ongoing and future environmental changes.

Meta-omic evaluation of bacterial microbial community structure and activity for the environmental assessment of soils: overcoming protein extraction pitfalls

Microorganisms play unique, essential and integral roles in the biosphere. This work aims to assess the utility of soil's metaomics for environmental diagnosis. Doñana National Park (DNP) was selected as a natural lab since it contains a strictly protected core that is surrounded by numerous threats of pollution. Culture-independent high-throughput molecular tools were used to evaluate the alterations of the global structure and metabolic activities of the microbiome. 16S rRNA sequencing shows lower bacterial abundance and diversity in areas historically exposed to contamination that surround DNP. For metaproteomics, an innovative post-alkaline protein extraction protocol was developed. After NaOH treatment, successive washing with Tris-HCl buffer supplemented with glycerol was essential to eliminate interferences. Starting from soils with different physicochemical characteristics, the method renders proteins with a remarkable resolution on SDS-PAGE gels. The proteins extracted were analysed by using an in-house database constructed from the rRNA data. LC-MS/MS analysis identified 2182 non-redundant proteins with 135 showing significant differences in relative abundance in the soils around DNP. Relevant global biological processes were altered in response to the environmental changes, such as protective and antioxidant mechanisms, translation, folding and homeostasis of proteins, membrane transport and aerobic respiratory metabolism.

The multidimensionality of soil macroecology

The recent past has seen a tremendous surge in soil macroecological studies and new insights into the global drivers of one-quarter of the biodiversity of the Earth. Building on these important developments, a recent paper in Global Ecology and Biogeography outlined promising methods and approaches to advance soil macroecology. Among other recommendations, White and colleagues introduced the concept of a spatial three-dimensionality in soil macroecology by considering the different spheres of influence and scales, as soil organism size ranges vary from bacteria to macro- and megafauna. Here, we extend this concept by discussing three additional dimensions (biological, physical, and societal) that are crucial to steer soil macroecology from pattern description towards better mechanistic understanding. In our view, these are the requirements to establish it as a predictive science that can inform policy about relevant nature and management conservation actions. We highlight the need to explore temporal dynamics of soil biodiversity and functions across multiple temporal scales, integrating different facets of biodiversity (i.e., variability in body size, life-history traits, species identities, and groups of taxa) and their relationships to multiple ecosystem functions, in addition to the feedback effects between humans and soil biodiversity. We also argue that future research needs to consider effective soil conservation policy and management in combination with higher awareness of the contributions of soil-based nature's contributions to people. To verify causal relationships, soil macroecology should be paired with local and globally distributed experiments. The present paper expands the multidimensional perspective on soil macroecology to guide future research contents and funding. We recommend considering these multiple dimensions in projected global soil biodiversity monitoring initiatives.

The diversity of decay

To predict how species loss will affect ecosystems, it is important to consider how biodiversity influences processes such as decomposition.