Helaina Black

Discontinuity in the responses of ecosystem processes and multifunctionality to altered soil community composition

Significance Ecosystem functioning is more strongly affected by biodiversity loss when multiple functions are considered because different species affect different functions. To quantify these biodiversity-functioning relationships, the emerging multifunctionality framework advocates calculation of indices that aggregate responses of individual functions. Data aggregation, however, is notorious for providing misleading information by obscuring true relationships between explanatory and response variables. We test the ability of common multifunctionality indices to reveal effects on key ecosystem functions of changes in soil communities. The multifunctionality indices all decrease with soil animal loss, but the responses of individual functions diverge markedly from these aggregated metrics. Application of the multifunctionality framework for landscape provision of multiple ecosystem services should therefore emphasize understanding relationships between communities and individual functions. Ecosystem management policies increasingly emphasize provision of multiple, as opposed to single, ecosystem services. Management for such “multifunctionality” has stimulated research into the role that biodiversity plays in providing desired rates of multiple ecosystem processes. Positive effects of biodiversity on indices of multifunctionality are consistently found, primarily because species that are redundant for one ecosystem process under a given set of environmental conditions play a distinct role under different conditions or in the provision of another ecosystem process. Here we show that the positive effects of diversity (specifically community composition) on multifunctionality indices can also arise from a statistical fallacy analogous to Simpson’s paradox (where aggregating data obscures causal relationships). We manipulated soil faunal community composition in combination with nitrogen fertilization of model grassland ecosystems and repeatedly measured five ecosystem processes related to plant productivity, carbon storage, and nutrient turnover. We calculated three common multifunctionality indices based on these processes and found that the functional complexity of the soil communities had a consistent positive effect on the indices. However, only two of the five ecosystem processes also responded positively to increasing complexity, whereas the other three responded neutrally or negatively. Furthermore, none of the individual processes responded to both the complexity and the nitrogen manipulations in a manner consistent with the indices. Our data show that multifunctionality indices can obscure relationships that exist between communities and key ecosystem processes, leading us to question their use in advancing theoretical understanding—and in management decisions—about how biodiversity is related to the provision of multiple ecosystem services.

REVIEW: The role of ecosystems and their management in regulating climate, and soil, water and air quality

1. Ecosystems have a critical role in regulating climate, and soil, water and air quality, but management to change an ecosystem process in support of one regulating ecosystem service can either provide co-benefits to other services or can result in trade-offs. 2. We examine the role of ecosystems in delivering these regulating ecosystem services, using the UK as our case study region. We identify some of the main co-benefits and trade-offs of ecosystem management within, and across, the regulating services of climate regulation, and soil, water and air quality regulation, and where relevant, we also describe interactions with other ecosystem services. Our analysis clearly identifies the many important linkages between these different ecosystem services. 3. However, soil, water and air quality regulation are often governed by different legislation or are under the jurisdiction of different regulators, which can make optimal management difficult to identify and to implement. Policies and legislation addressing air, water and soil are sometimes disconnected, with no integrated overview of how these policies interact. This can lead to conflicting messages regarding the use and management of soil, water and air. Similarly, climate change legislation is separate from that aiming to protect and enhance soil, water and air quality, leading to further potential for policy conflict. 4. All regulating services, even if they are synergistic, may trade off against other ecosystem services. At a policy level, this may well be the biggest conflict. The fact that even individual regulating services comprise multiple and contrasting indicators (e.g. the various components of water quality such as nutrient levels, acidity, pathogens and sediments), adds to the complexity of the challenge. 5. Synthesis and applications. We conclude that although there are some good examples of integrated ecosystem management, some aspects of ecosystem management could be better coordinated to deliver multiple ecosystem services, and that an ecosystem services framework to assess co-benefits and trade-offs would help regulators, policy-makers and ecosystem managers to deliver more coherent ecosystem management strategies. In this way, an ecosystem services framework may improve the regulation of climate, and soil, water and air quality, even in the absence of economic valuation of the individual services.

An inter-laboratory comparison of multi-enzyme and multiple substrate-induced respiration assays to assess method consistency in soil monitoring

The use of indicators in soil monitoring schemes to detect changes in soil quality is receiving increased attention, particularly the application of soil biological methods. However, to date, the ability to compare information from different laboratories applying soil microbiological techniques in broad-scale monitoring has rarely been taken into account. This study aimed to assess the consistency and repeatability of two techniques that are being evaluated for use as microbiological indicators of soil quality: multi-enzyme activity assay and multiple substrate-induced respiration (MSIR). Data were tested for intrinsic (within-assay plate) variation, inter-laboratory repeatability (geometric mean regression and correlation coefficient) and land-use discrimination (principal components analysis). Intrinsic variation was large for both assays suggesting that high replicate numbers are required. Inter-laboratory repeatability showed diverging patterns for the enzyme assay and MSIR. Discrimination of soils was significant for both techniques with relatively consistent patterns; however, combined laboratory discrimination analyses for each technique showed inconsistent correspondence between the laboratories. These issues could be addressed through the adoption of reliable analytical standards for biological methods along with adequate replication. However, until the former is addressed, dispersed analyses are not currently advisable for monitoring schemes.

Impact of water table depth on forest soil methane turnover in laboratory soil cores deduced from natural abundance and tracer 13C stable isotope experiments

We investigated turnover of methane (CH4) in soils from a poorly drained UK forest. In situ, this forest exhibited a negligible soil–atmosphere CH4 flux, whereas adjacent grassland plots were sources of CH4. We hypothesised that the forest plots exhibited reduced anaerobic CH4 production through water-table draw down. Consequently, we exposed soil cores from under oak to high and low water-table conditions in the laboratory. Methane fluxes increased significantly in the high water-table (1925±1702 μg CH4 m−2 h−1) compared to the low one (−3.5±6.8 μg CH4 m−2 h−1). Natural abundance δ13C values of CH4 showed a strong depletion in high water-table cores (−56.7±2.9 ‰) compared to methane in ambient air (−46.0 ‰) indicative of methanogenic processes. The δ13C values of CH4 from low water-table cores (δ13C−46.8±0.2 ‰) was similar to ambient air and suggested little alteration of headspace CH4 by the soil microbial community. In order to assess the CH4 oxidizing activity of the two treatments conclusively, a 13CH4 spike was added to the cores and 13CO2 production was measured as the by-product of CH4 oxidation. 13CH4 oxidation rates were 57.5 (±12.7) and 0.5 (±0.1) μg CH4 m−2 h−1 for high and low water-tables, respectively. These data show that the lower water-table hydrology treatment impacted methanogenic processes without stimulating methanotrophy.

Reply to Byrnes et al.: Aggregation can obscure understanding of ecosystem multifunctionality

We manipulated soil animal communities in combination with nitrogen fertilization and found that individual grassland ecosystem functions had contrasting responses across the manipulations (1). We therefore cautioned against using a single multifunctionality index that aggregates individual functions to characterize overall ecosystem functioning (1).

E-SMART: Environmental Sensing for Monitoring and Advising in Real-Time

Smart monitoring, using real-time environmental sensing with links to server-side data processing/modeling, allows progression from data acquisition to useful information generation. The use of modern technology such as mobile phones to provide imagery and other types of data along with GPS-derived coordinates enables researchers and stakeholders to integrate ground-based observations with existing datasets. We have developed an infrastructure linking mobile communications, server-side processing and storage of data and imagery, and field-based access to existing spatial datasets. This infrastructure has been used for the development of a number of mobile phone apps (applications) and web-based applications, and has proved useful for stakeholders in agriculture, science and policy. In addition to giving information on the capacity development, we demonstrate useful applications relating to the upload, interpretation and integration of data (e.g. automated interpretation of soil profile imagery, carbon content estimation from soil colour) while focusing on the technical aspects of the underpinning system.

Relative importance of local- and large-scale drivers of alpine soil microarthropod communities

Nitrogen (N) deposition and climate are acknowledged drivers of change in biodiversity and ecosystem function at large scales. However, at a local scale, their impact on functions and community structure of organisms is filtered by drivers like habitat quality and food quality/availability. This study assesses the relative impact of large-scale factors, N deposition and climate (rainfall and temperature), versus local-scale factors of habitat quality and food quality/availability on soil fauna communities at 15 alpine moss–sedge heaths along an N deposition gradient in the UK. Habitat quality and food quality/availability were the primary drivers of microarthropod communities. No direct impacts of N deposition on the microarthropod community were observed, but induced changes in habitat quality (decline in moss cover and depth) and food quality (decreased vegetation C:N) associated with increased N deposition strongly suggest an indirect impact of N. Habitat quality and climate explained variation in the composition of the Oribatida, Mesostigmata, and Collembola communities, while only habitat quality significantly impacted the Prostigmata. Food quality and prey availability were important in explaining the composition of the oribatid and mesostigmatid mite communities, respectively. This study shows that, in alpine habitats, soil microarthropod community structure responds most strongly to local-scale variation in habitat quality and food availability rather than large-scale variation in climate and pollution. However, given the strong links between N deposition and the key habitat quality parameters, we conclude that N deposition indirectly drives changes in the soil microarthropod community, suggesting a mechanism by which large-scale drivers indirectly impacts these functionally important groups.

EXPRESS: Exploring the impact of different input data types on soil variable estimation using the ICRAF-ISRIC global soil spectral database

Using the International Centre for Research in Agroforestry–International Soil Reference and Information Centre (ICRAF-ISRIC) global soil spectroscopy database, models were developed to estimate a number of soil variables using different input data types. These input types included: (1) site data only; (2) visible–near-infrared (Vis-NIR) diffuse reflectance spectroscopy only; (3) combined site and Vis-NIR data; (4) red–green–blue (RGB) color data only; and (5) combined site and RGB color data. The models produced variable estimation accuracy, with RGB only being generally worst and spectroscopy plus site being best. However, we showed that for certain variables, estimation accuracy levels achieved with the “site plus RGB input data” were sufficiently good to provide useful estimates (r2 > 0.7). These included major elements (Ca, Si, Al, Fe), organic carbon, and cation exchange capacity. Estimates for bulk density, contrast-to-noise (C/N), and P were moderately good, but K was not well estimated using this model type. For the “spectra plus site” model, many more variables were well estimated, including many that are important indicators for agricultural productivity and soil health. Sum of cation, electrical conductivity, Si, Ca, and Al oxides, and C/N ratio were estimated using this approach with r2 values > 0.9. This work provides a mechanism for identifying the cost-effectiveness of using different model input data, with associated costs, for estimating soil variables to required levels of accuracy.

Advances in Soil Biology: What does this mean for assessing soil change?

Our interests in soil change are moving away from soil properties and increasingly towards changes in the processes and functioning of soils. Soil organisms are fundamental to dynamics and change in soils through their fundamental role in soil processes [1]. However it is only with recent technical and theoretical advances that we have started to establish quantitative relationships between soil biology and soil change (c.f. [2]). It is this predictive understanding that will enable us to fully integrate soil biology into the effective monitoring and sustainable management of soils. This paper outlines some of the recent advances in soil biology and discusses their relevance to monitoring and management.