Accounting for multiple ecosystem services in a simulation of land-use decisions: Does it reduce tropical deforestation?

Conversion of tropical forests is among the primary causes of global environmental change. The loss of their important environmental services has prompted calls to integrate ecosystem services (ES) in addition to socio-economic objectives in decision-making. To test the effect of accounting for both ES and socio-economic objectives in land-use decisions, we develop a new dynamic approach to model deforestation scenarios for tropical mountain forests. We integrate multi-objective optimization of land allocation with an innovative approach to consider uncertainty spaces for each objective. These uncertainty spaces account for potential variability among decision-makers, who may have different expectations about the future. When optimizing only socio-economic objectives, the model continues the past trend in deforestation (1975-2015) in the projected land-use allocation (2015-2070). Based on indicators for biomass production, carbon storage, climate and water regulation, and soil quality, we show that considering multiple ES in addition to the socio-economic objectives has heterogeneous effects on land-use allocation. It saves some natural forest if the natural forest share is below 38%, and can stop deforestation once the natural forest share drops below 10%. For landscapes with high shares of forest (38%-80% in our study), accounting for multiple ES under high uncertainty of their indicators may, however, accelerate deforestation. For such multifunctional landscapes, two main effects prevail: (a) accelerated expansion of diversified non-natural areas to elevate the levels of the indicators and (b) increased landscape diversification to maintain multiple ES, reducing the proportion of natural forest. Only when accounting for vascular plant species richness as an explicit objective in the optimization, deforestation was consistently reduced. Aiming for multifunctional landscapes may therefore conflict with the aim of reducing deforestation, which we can quantify here for the first time. Our findings are relevant for identifying types of landscapes where this conflict may arise and to better align respective policies.

Tracing the fate and transport of secondary plant metabolites in a laboratory mesocosm experiment by employing mass spectrometric imaging.

Mass spectrometric imaging (MSI) has received considerable attention in recent years, since it allows the molecular mapping of various compound classes, such as proteins, peptides, glycans, secondary metabolites, lipids, and drugs in animal, human, or plant tissue sections. In the present study, the application of laser-based MSI analysis of secondary plant metabolites to monitor their transport from the grass leaves of Dactylis glomerata, over the crop of the grasshopper Chorthippus dorsatus to its excrements, and finally in the soil solution is described. This plant-herbivore-soil pathway was investigated under controlled conditions by using laboratory mesocosms. From six targeted secondary plant metabolites (dehydroquinic acid, quinic acid, apigenin, luteolin, tricin, and rosmarinic acid), only quinic acid, and dehydroquinic acid, an in-source-decay (ISD) product of quinic acid, could be traced in nearly all compartments. The tentative identification of secondary plant metabolites was performed by MS/MS analysis of methanol extracts prepared from the investigated compartments, in both the positive and negative ion mode, and subsequently compared with the results generated from the reference standards. Except for tricin, all secondary metabolites could be tentatively identified by this approach. Additional liquid-chromatography mass spectrometry (LC-MS) experiments were carried out to verify the MSI results and revealed the presence of quinic acid only in grass and chewed grass, whereas apigenin-hexoside-pentoside and luteolin-hexoisde-pentoside could be traced in the grasshopper body and excrement extracts. In summary, the MSI technique shows a trade-off between sensitivity and spatial resolution. Graphical abstract Monitoring quinic acid in a mesocosm experiment by mass spectrometric imaging (MSI).

Land-use and soil depth affect resource and microbial stoichiometry in a tropical mountain rainforest region of southern Ecuador.

Global change phenomena, such as forest disturbance and land-use change, significantly affect elemental balances as well as the structure and function of terrestrial ecosystems. However, the importance of shifts in soil nutrient stoichiometry for the regulation of belowground biota and soil food webs have not been intensively studied for tropical ecosystems. In the present account, we examine the effects of land-use change and soil depth on soil and microbial stoichiometry along a land-use sequence (natural forest, pastures of different ages, secondary succession) in the tropical mountain rainforest region of southern Ecuador. Furthermore, we analyzed (PLFA-method) whether shifts in the microbial community structure were related to alterations in soil and microbial stoichiometry. Soil and microbial stoichiometry were affected by both land-use change and soil depth. After forest disturbance, significant decreases of soil C:N:P ratios at the pastures were followed by increases during secondary succession. Microbial C:N ratios varied slightly in response to land-use change, whereas no fixed microbial C:P and N:P ratios were observed. Shifts in microbial community composition were associated with soil and microbial stoichiometry. Strong positive relationships between PLFA-markers 18:2n6,9c (saprotrophic fungi) and 20:4 (animals) and negative associations between 20:4 and microbial N:P point to land-use change affecting the structure of soil food webs. Significant deviations from global soil and microbial C:N:P ratios indicated a major force of land-use change to alter stoichiometric relationships and to structure biological systems. Our results support the idea that soil biotic communities are stoichiometrically flexible in order to adapt to alterations in resource stoichiometry.

Tapping the Full Potential of Infrared Spectroscopy for the Analysis of Technical Lignins.

We present an approach to overcome the challenges associated with the increasing demand of high-throughput characterization of technical lignins, a key resource in emerging bioeconomies. Our approach offers a resort from the lack of direct, simple, and low-cost analytical techniques for lignin characterization by employing multivariate calibration models based on infrared (IR) spectroscopy to predict structural properties of lignins (i. e., functionality, molar mass). By leveraging a comprehensive database of over 500 well-characterized technical lignin samples - a factor of 10 larger than previously used sets - our chemometric models achieved high levels of quality and statistical confidence for the determination of different functional group contents (RMSEPs of 4-16 %). However, the statistical moments of the molar mass distribution are still best determined by size-exclusion chromatography. Analyses of over 500 technical lignins offered also a great opportunity to provide information on the general variability in kraft lignins and lignosulfonates (from different origins). Overall, the effected savings in analysis time (>7 h), resources, and required sample mass combined with non-destructiveness of the measurement satisfy key demands for efficient high-throughput lignin analyses. Finally, we discuss the advantages, disadvantages, and limitations of our approach, along with critical insights into the associated chemical-analytical and spectroscopic challenges.

Seasonal Patterns of Dominant Microbes Involved in Central Nutrient Cycles in the Subsurface.

Microbial communities play a key role for central biogeochemical cycles in the subsurface. Little is known about whether short-term seasonal drought and rewetting events influence the dominant microbes involved in C- and N-cycles. Here, we applied metaproteomics at different subsurface sites in winter, summer and autumn from surface litter layer, seepage water at increasing subsoil depths and remote located groundwater from two wells within the Hainich Critical Zone Exploratory, Germany. We observed changes in the dominance of microbial families at subsurface sampling sites with increasing distances, i.e., Microcoleaceae dominated in topsoil seepage, while Candidatus Brocadiaceae dominated at deeper and more distant groundwater wells. Nitrifying bacteria showed a shift in dominance from drought to rewetting events from summer by Nitrosomandaceae to autumn by Candidatus Brocadiaceae. We further observed that the reductive pentose phosphate pathway was a prominent CO2-fixation strategy, dominated by Woeseiaceae in wet early winter, which decreased under drought conditions and changed to a dominance of Sphingobacteriaceae under rewetting conditions. This study shows that increasing subsurface sites and rewetting event after drought alter the dominances of key subsurface microbes. This helps to predict the consequences of annual seasonal dynamics on the nutrient cycling microbes that contribute to ecosystem functioning.

Land-use and fire drive temporal patterns of soil solution chemistry and nutrient fluxes.

Land-use type and ecosystem disturbances are important drivers for element cycling and bear the potential to modulate soil processes and hence ecosystem functions. To better understand the effect of such drivers on the magnitude and temporal patterns of organic matter (OM) and associated nutrient fluxes in soils, continuous flux monitoring is indispensable but insufficiently studied yet. We conducted a field study to elucidate the impact of land-use and surface fires on OM and nutrient fluxes with soil solution regarding seasonal and temporal patterns analyzing short (<3months) and medium-term (3-12months) effects. Control and prescribed fire-treated topsoil horizons in beech forests and pastures were monitored biweekly for dissolved and particulate OM (DOM, POM) and solution chemistry (pH value, elements: Ca, Mg, Na, K, Al, Fe, Mn, P, S, Si) over one post-fire year. Linear mixed model analyses exhibited that mean annual DOM and POM fluxes did not differ between the two land-use types, but were subjected to strong seasonal patterns. Fire disturbance significantly lowered the annual soil solution pH in both land-uses and increased water fluxes, while DOC fluxes remained unaffected. A positive response of POC and S to fire was limited to short-term effects, while amplified particulate and dissolved nitrogen fluxes were observed in the longer run and co-ocurred with accelerated Ca and Mg fluxes. In summary, surface fires generated stronger effects on element fluxes than the land-use. Fire-induced increases in POM fluxes suggest that the particulate fraction represent a major pathway of OM translocation into the subsoil and beyond. With regard to ecosystem functions, pasture ecosystems were less prone to the risk of nutrient losses following fire events than the forest. In pastures, fire-induced base cation export may accelerate soil acidification, consequently exhausting soil buffer systems and thus may reduce the resilience to acidic depositions and disturbances.

Proteome data on the microbial microbiome of grasshopper feces.

We present proteome data from the microbiota (feces) after a diet shift from a natural diverse to a monocultural meadow with Dactylis glomerata. The abundant grasshopper species, Chorthippus dorsatus, was taken from the wild and kept in captivity and were fed with Dactylis glomerata for five days. For phytophagous insects, the efficiency of utilization of hemicellulose and cellulose depends on the gut microbiota. Shifts in environmental and management conditions alter the presence and abundance of plant species which may induce adaptations in the diversity of gut microbiota. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD005126.

Fire enhances solubility of biogenic silica.

Changing fire regimes in response to climate change are likely to have significant effects on terrestrial ecosystems and biogeochemical cycles. While effects of fire on some nutrient cycles have been quite well-studied, little attention has been paid to the silicon cycle. We used an alkaline continuous extraction to examine changes in the quantity and characteristics of alkaline extractable Si (AlkExSi) after applying two burning treatments (no heating, 350°C and 550°C) to three types of organic soil material (from spruce forest, beech forest and a commercial peat). The total AlkExSi measured was 25.1±2.1mgg-1 and 15.4±0.9mgg-1 for spruce and beech respectively, and 1.2±0.5mgg-1 for peat. The alkaline extraction parameters confirm a purely biogenic AlkExSi source in untreated spruce and beech organic soil material samples. Organic soil material of beech forest had two biogenic silica pools, differing in reactivity during alkaline extraction. Burning severely alters the alkaline dissolution parameters suggesting a significant crystallization of biogenic Si (BSi) with increased burning severity. Additionally, dissolution experiments carried out in rain water showed that fire increased the solubility of BSi by a factor of 40 and 20 in the case of the spruce and beech organic soil material respectively. The extent of enhanced Si solubility appears to be a trade-off function between organic matter losses and degree of crystallization. The burned soils could provide a strong and immediate Si source for the environment. In situ ecosystem characteristics that affect the uptake-leaching balance will determine the fate of the dissolved Si. Ecosystems low in BSi, like Sphagnum peatland, will not show drastic alteration in the Si cycle due to fire.

Microbes as Engines of Ecosystem Function: When Does Community Structure Enhance Predictions of Ecosystem Processes?

Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.