Showing papers by "Alexandra Weigelt published in 2019"

The Future of Complementarity: Disentangling Causes from Consequences

Abstract: Evidence suggests that biodiversity supports ecosystem functioning. Yet, the mechanisms driving this relationship remain unclear. Complementarity is one common explanation for these positive biodiversity–ecosystem functioning relationships. Yet, complementarity is often indirectly quantified as overperformance in mixture relative to monoculture (e.g., ‘complementarity effect’). This overperformance is then attributed to the intuitive idea of complementarity or, more specifically, to species resource partitioning. Locally, however, several unassociated causes may drive this overperformance. Here, we differentiate complementarity into three types of species differences that may cause enhanced ecosystem functioning in more diverse ecosystems: (i) resource partitioning, (ii) abiotic facilitation, and (iii) biotic feedbacks. We argue that disentangling these three causes is crucial for predicting the response of ecosystems to future biodiversity loss.

Persistence of dissolved organic matter explained by molecular changes during its passage through soil

Abstract: Dissolved organic matter affects fundamental biogeochemical processes in the soil such as nutrient cycling and organic matter storage. The current paradigm is that processing of dissolved organic matter converges to recalcitrant molecules (those that resist degradation) of low molecular mass and high molecular diversity through biotic and abiotic processes. Here we demonstrate that the molecular composition and properties of dissolved organic matter continuously change during soil passage and propose that this reflects a continual shifting of its sources. Using ultrahigh-resolution mass spectrometry and nuclear magnetic resonance spectroscopy, we studied the molecular changes of dissolved organic matter from the soil surface to 60 cm depth in 20 temperate grassland communities in soil type Eutric Fluvisol. Applying a semi-quantitative approach, we observed that plant-derived molecules were first broken down into molecules containing a large proportion of low-molecular-mass compounds. These low-molecular-mass compounds became less abundant during soil passage, whereas larger molecules, depleted in plant-related ligno-cellulosic structures, became more abundant. These findings indicate that the small plant-derived molecules were preferentially consumed by microorganisms and transformed into larger microbial-derived molecules. This suggests that dissolved organic matter is not intrinsically recalcitrant but instead persists in soil as a result of simultaneous consumption, transformation and formation. Dissolved organic matter is persistent in soil owing to continuous consumption and transformation rather than owing to its recalcitrant molecular properties, according to analyses of molecular changes of dissolved organic matter as it passes through soil.

Multiple plant diversity components drive consumer communities across ecosystems

Abstract: Humans modify ecosystems and biodiversity worldwide, with negative consequences for ecosystem functioning. Promoting plant diversity is increasingly suggested as a mitigation strategy. However, our mechanistic understanding of how plant diversity affects the diversity of heterotrophic consumer communities remains limited. Here, we disentangle the relative importance of key components of plant diversity as drivers of herbivore, predator, and parasitoid species richness in experimental forests and grasslands. We find that plant species richness effects on consumer species richness are consistently positive and mediated by elevated structural and functional diversity of the plant communities. The importance of these diversity components differs across trophic levels and ecosystems, cautioning against ignoring the fundamental ecological complexity of biodiversity effects. Importantly, plant diversity effects on higher trophic-level species richness are in many cases mediated by modifications of consumer abundances. In light of recently reported drastic declines in insect abundances, our study identifies important pathways connecting plant diversity and consumer diversity across ecosystems.

A multitrophic perspective on biodiversity-ecosystem functioning research

Abstract: Concern about the functional consequences of unprecedented loss in biodiversity has prompted biodiversity–ecosystem functioning (BEF) research to become one of the most active fields of ecological research in the past 25 years. Hundreds of experiments have manipulated biodiversity as an independent variable and found compelling support that the functioning of ecosystems increases with the diversity of their ecological communities. This research has also identified some of the mechanisms underlying BEF relationships, some context-dependencies of the strength of relationships, as well as implications for various ecosystem services that humankind depends upon. In this chapter, we argue that a multitrophic perspective of biotic interactions in random and non-random biodiversity change scenarios is key to advance future BEF research and to address some of its most important remaining challenges. We discuss that the study and the quantification of multitrophic interactions in space and time facilitates scaling up from small-scale biodiversity manipulations and ecosystem function assessments to management-relevant spatial scales across ecosystem boundaries. We specifically consider multitrophic conceptual frameworks to understand and predict the context-dependency of BEF relationships. Moreover, we highlight the importance of the eco-evolutionary underpinnings of multitrophic BEF relationships. We outline that FAIR data (meeting the standards of findability, accessibility, interoperability, and reusability) and reproducible processing will be key to advance this field of research by making it more integrative. Finally, we show how these BEF insights may be implemented for ecosystem management, society, and policy. Given that human well-being critically depends on the multiple services provided by diverse, multitrophic communities, integrating the approaches of evolutionary ecology, community ecology, and ecosystem ecology in future BEF research will be key to refine conservation targets and develop sustainable management strategies.

Plant species richness and functional groups have different effects on soil water content in a decade‐long grassland experiment

Abstract: The temporal and spatial dynamics of soil water are closely interlinked with terrestrial ecosystems functioning. The interaction between plant community properties such as species composition and richness and soil water mirrors fundamental ecological processes determining above-ground–below-ground feedbacks. Plant–water relations and water stress have attracted considerable attention in biodiversity experiments. Yet, although soil scientific research suggests an influence of ecosystem productivity on soil hydraulic properties, temporal changes of the soil water content and soil hydraulic properties remain largely understudied in biodiversity experiments. Thus, insights on how plant diversity—productivity relationships affect soil water are lacking. Here, we determine which factors related to plant community composition (species and functional group richness, presence of plant functional groups) and soil (organic carbon concentration) affect soil water in a long-term grassland biodiversity experiment (The Jena Experiment). Both plant species richness and the presence of particular functional groups affected soil water content, while functional group richness played no role. The effect of species richness changed from positive to negative and expanded to deeper soil with time. Shortly after establishment, increased topsoil water content was related to higher leaf area index in species-rich plots, which enhanced shading. In later years, higher species richness increased topsoil organic carbon, likely improving soil aggregation. Improved aggregation, in turn, dried topsoils in species-rich plots due to faster drainage of rainwater. Functional groups affected soil water distribution, likely due to plant traits affecting root water uptake depths, shading, or water-use efficiency. For instance, topsoils in plots containing grasses were generally drier, while plots with legumes were moister. Synthesis. Our decade-long experiment reveals that the maturation of grasslands changes the effects of plant richness from influencing soil water content through shading effects to altering soil physical characteristics in addition to modification of water uptake depth. Functional groups affected the soil water distribution by characteristic shifts of root water uptake depth, but did not enhance exploitation of the overall soil water storage. Our results reconcile previous seemingly contradictory results on the relation between grassland species diversity and soil moisture and highlight the role of vegetation composition for soil processes.

The results of biodiversity-ecosystem functioning experiments are realistic

Abstract: Summary A large body of research shows that biodiversity loss can reduce ecosystem functioning, thus providing support for the conservation of biological diversity1–4. Much of the evidence for this relationship is drawn from biodiversity-ecosystem functioning experiments (hereafter: biodiversity experiments), in which biodiversity loss is simulated by randomly assembling communities of varying species diversity, and ecosystem functions are measured5–9. This random assembly has led some ecologists to question the relevance of biodiversity experiments to real-world ecosystems, where community assembly may often be non-random and influenced by external drivers, such as climate or land-use intensification10–18. Despite these repeated criticisms, there has been no comprehensive, quantitative assessment of how experimental and real-world plant communities really differ, and whether these differences invalidate the experimental results. Here, we compare data from two of the largest and longest-running grassland biodiversity experiments globally (Jena Experiment, Germany; BioDIV, USA) to related real-world grassland plant communities in terms of their taxonomic, functional, and phylogenetic diversity and functional-trait composition. We found that plant communities of biodiversity experiments have greater variance in these compositional features than their real-world counterparts, covering almost all of the variation of the real-world communities (82-96%) while also containing community types that are not currently observed in the real world. We then re-analysed a subset of experimental data that included only ecologically-realistic communities, i.e. those comparable to real-world communities. For ten out of twelve biodiversity-ecosystem functioning relationships, biodiversity effects did not differ significantly between the full dataset of biodiversity experiments and the ecologically-realistic subset of experimental communities. This demonstrates that the results of biodiversity experiments are largely insensitive to the inclusion/exclusion of unrealistic communities. By bridging the gap between experimental and real-world studies, these results demonstrate the validity of inferences from biodiversity experiments, a key step in translating their results into specific recommendations for real-world biodiversity management.

Chapter One - A multitrophic perspective on biodiversity–ecosystem functioning research

Abstract: Concern about the functional consequences of unprecedented loss in biodiversity has prompted biodiversity-ecosystem functioning (BEF) research to become one of the most active fields of ecological research in the past 25 years. Hundreds of experiments have manipulated biodiversity as an independent variable and found compelling support that the functioning of ecosystems increases with the diversity of their ecological communities. This research has also identified some of the mechanisms underlying BEF relationships, some context-dependencies of the strength of relationships, as well as implications for various ecosystem services that mankind depends upon. In this paper, we argue that a multitrophic perspective of biotic interactions in random and non-random biodiversity change scenarios is key to advance future BEF research and to address some of its most important remaining challenges. We discuss that the study and the quantification of multitrophic interactions in space and time facilitates scaling up from small-scale biodiversity manipulations and ecosystem function assessments to management-relevant spatial scales across ecosystem boundaries. We specifically consider multitrophic conceptual frameworks to understand and predict the context-dependency of BEF relationships. Moreover, we highlight the importance of the eco-evolutionary underpinnings of multitrophic BEF relationships. We outline that FAIR data (meeting the standards of findability, accessibility, interoperability, and reusability) and reproducible processing will be key to advance this field of research by making it more integrative. Finally, we show how these BEF insights may be implemented for ecosystem management, society, and policy. Given that human well-being critically depends on the multiple services provided by diverse, multitrophic communities, integrating the approaches of evolutionary ecology, community ecology, and ecosystem ecology in future BEF research will be key to refine conservation targets and develop sustainable management strategies.

Extensive grassland-use sustains high levels of soil biological activity, but does not alleviate detrimental climate change effects

Abstract: Climate change and intensified land use simultaneously affect the magnitude and resilience of soil-derived ecosystem functions, such as nutrient cycling and decomposition. Thus far, the responses of soil organisms to interacting global change drivers remain poorly explored and our knowledge of below-ground phenology is particularly limited. Previous studies suggest that extensive land-use management has the potential to buffer detrimental climate change impacts, via biodiversity-mediated effects. According to the insurance hypothesis of biodiversity, a higher biodiversity of soil communities and thus an elevated response diversity to climate change would facilitate a more stable provisioning of ecosystem functions under environmental stress. Here we present results of a two-year study investigating, at fine temporal resolution, the effects of predicted climate change scenarios (altered precipitation patterns; passive warming) on three grassland types, differing in land-use intensity, soil biological activity, and in resilience. We show that future climate conditions consistently reduced soil biological activity, revealing an overall negative effect of predicted climate change. Furthermore, future climate caused earlier and significantly lower peaks of biological activity in the soil. Land-use intensity also significantly decreased soil biological activity, but contrary to general expectations, extensive land use did not alleviate the detrimental effects of simulated climate change. Instead, the greatest reduction in soil biological activity was observed in extensively-used grasslands, highlighting their potential vulnerability to predicted climate change. To assure high levels of biological activity in resilient agroecosystems, extensive land use needs to be complemented by other management approaches, such as the adoption of specific plant species compositions that secure ecosystem functioning in a changing world.

Fine root lignin content is well predictable with near-infrared spectroscopy.

Abstract: 1. Root lignin is a key driver of root decomposition, which in turn is a fundamental component of the terrestrial carbon cycle and increasingly in the focus of ecologists and global climate change research. However, measuring lignin content is labor-intensive and therefore not well-suited to handle the large sample sizes of most ecological studies. To overcome this bottleneck, we explored the applicability of high-throughput near infrared spectroscopy (NIRS) measurements to predict fine root lignin content. 2. We measured fine root lignin content in 73 plots of a field biodiversity experiment containing a pool of 60 grassland species using the Acetylbromid (AcBr) method. To predict lignin content, we established NIRS calibration and prediction models based on partial least square regression (PLSR) resulting in moderate prediction accuracies (RPD = 1.96, R2 = 0.74, RMSE = 3.79). 3. In a second step, we combined PLSR with spectral variable selection. This considerably improved model performance (RPD = 2.67, R2 = 0.86, RMSE = 2.78) and enabled us to identify chemically meaningful wavelength regions for lignin prediction. 4. We identified 38 case studies in a literature survey and quantified median model performance parameters from these studies as a benchmark for our results. Our results show that the combination Acetylbromid extracted lignin and NIR spectroscopy is well suited for the rapid analysis of root lignin contents in herbaceous plant species even if the amount of sample is limited.

Lost in trait space: species-poor communities are inflexible in properties that drive ecosystem functioning

Abstract: It is now well established that biodiversity plays an important role in determining ecosystem functioning and its stability over time. A possible mechanism for this positive effect of biodiversity is that more diverse plant communities have a greater capacity to respond to environmental changes through shifts in species dominance and composition. In our study, we utilized data from five long-term grassland biodiversity experiments located in North America (three studies) and Central Europe (two studies), in which plant species richness and global change drivers were manipulated simultaneously. The global change drivers included warming, drought, elevated atmospheric CO2 concentrations, elevated N inputs, or intensive management. Across drivers, functional change over time was significantly greater for communities of high plant diversity than that of low diversity because of a higher functional and phylogenetic richness and mostly associated with a dominance by species with a ‘slow and tall’ strategy. Community functional shifts in response to global change drivers were, however, relatively weak and mostly not influenced by diversity. The exception to this was warming, where diverse communities showed stronger shifts than species-poor communities. Our results confirm the hypothesis that diverse communities have a greater capacity for functional change than species-poor communities, particularly in their successional dynamics, but also potentially in their responses to environmental change. This capacity could underlie the positive biodiversity-stability relationship and buffer ecosystem responses to environmental change.

Above- and belowground overyielding are related at the community and species level in a grassland biodiversity experiment

Abstract: Plant species richness positively affects plant productivity both above- and belowground. While this suggests that they are related at the community level, few studies have calculated above- and belowground overyielding simultaneously. It thus remains unknown whether above- and belowground overyielding are correlated. Moreover, it is unknown how belowground community level overyielding translates to the species level. We investigated above- and belowground overyielding in the Jena Trait-Based Biodiversity Experiment, at both the community and species level and across two 8-species pools. We found that above- and belowground overyielding were positively correlated at the community level and at the species level—for seven out of the 13 investigated species. Some plant species performed better in mixtures compared to monocultures and others performed worse, but the majority did so simultaneously above- and belowground. However, plants invested more in aboveground overyielding than belowground. Based on this disproportional investment in overyielding aboveground, we conclude that light was more limiting than belowground resources in the present study, which requires individual species to compete more for light than for belowground resources.

Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships

Abstract: The functioning and service provisioning of ecosystems in the face of anthropogenic environmental and biodiversity change is a cornerstone of ecological research. The last three decades of biodiversity–ecosystem functioning (BEF) research have provided compelling evidence for the significant positive role of biodiversity in the functioning of many ecosystems. Despite broad consensus of this relationship, the underlying ecological and evolutionary mechanisms have not been well understood. This complicates the transition from a description of patterns to a predictive science. The proposed Research Unit aims at filling this gap of knowledge by applying novel experimental and analytical approaches in one of the longest-running biodiversity experiments in the world: the Jena Experiment. The central aim of the Research Unit is to uncover the mechanisms that determine BEF relationships in the short- and in the long-term. Increasing BEF relationships with time in long-term experiments do not only call for a paradigm shift in the appreciation of the relevance of biodiversity change, they likely are key to understanding the mechanisms of BEF relationships in general. The subprojects of the proposed Research Unit fall into two tightly linked main categories with two research areas each that aim at exploring variation in community assembly processes and resulting differences in biotic interactions as determinants of the long-term BEF relationship. Subprojects under “Microbial community assembly” and “Assembly and functions of animal communities” mostly focus on plant diversity effects on the assembly of communities and their feedback effects on biotic interactions and ecosystem functions. Subprojects under “Mediators of plant-biotic interactions” and “Intraspecific diversity and micro-evolutionary changes” mostly focus on plant diversity effects on plant trait expression and micro-evolutionary adaptation, and subsequent feedback effects on biotic interactions and ecosystem functions. This unification of evolutionary and ecosystem processes requires collaboration across the proposed subprojects in targeted plant and soil history experiments using cutting-edge technology and will produce significant synergies and novel mechanistic insights into BEF relationships. The Research Unit of the Jena Experiment is uniquely positioned in this context by taking an interdisciplinary and integrative approach to capture whole-ecosystem responses to changes in biodiversity and to advance a vibrant research field.

Terrestrial laser scanning reveals temporal changes in biodiversity mechanisms driving grassland productivity

Abstract: Biodiversity often enhances ecosystem functioning likely due to multiple, often temporarily separated drivers. Yet, most studies are based on one or two snapshot measurements per year. We estimated productivity using bi-weekly estimates of high-resolution canopy height in 2 years with terrestrial laser scanning (TLS) in a grassland diversity experiment. We measured how different facets of plant diversity (functional dispersion [FDis], functional identity [PCA species scores], and species richness [SR]) predict aboveground biomass over time. We found strong intra- and inter-annual variability in the relative importance of different mechanisms underlying the diversity effects on mean canopy height, i.e., resource partitioning (via FDis) and identity effects (via species scores), respectively. TLS is a promising tool to quantify community development non-destructively and to unravel the temporal dynamics of biodiversity-ecosystem functioning mechanisms. Our results show that harvesting at estimated peak biomass—as done in most grassland experiments—may miss important variation in underlying mechanisms driving cumulative biomass production.

rhizoTrak: a flexible open source Fiji plugin for user-friendly manual annotation of time-series images from minirhizotrons

Abstract: Minirhizotrons are commonly used to study root turnover which is essential for understanding ecosystem carbon and nutrient cycling. Yet, extracting data from minirhizotron images requires extensive annotation effort. Existing annotation tools often lack flexibility and provide only a subset of the required functionality. To facilitate efficient root annotation in minirhizotrons, we present the user-friendly open source tool rhizoTrak. rhizoTrak builds on TrakEM2 and is publicly available as Fiji plugin. It uses treelines to represent branching structures in roots and assigns customizable status labels per root segment. rhizoTrak offers configuration options for visualization and various functions for root annotation mostly accessible via keyboard shortcuts. rhizoTrak allows time-series data import and particularly supports easy handling and annotation of time-series images. This is facilitated via explicit temporal links (connectors) between roots which are automatically generated when copying annotations from one image to the next. rhizoTrak includes automatic consistency checks and guided procedures for resolving inconsistencies. It facilitates easy data exchange with other software by supporting open data formats. rhizoTrak covers the full range of functions required for user-friendly and efficient annotation of time-series images. Its flexibility and open source nature will foster efficient data acquisition procedures in root studies using minirhizotrons.

rhizoTrak: A flexible open source Fiji plugin for user-friendly manual annotation of time-series images from minirhizotrons

Abstract: Background and aims Minirhizotrons are commonly used to study root turnover which is essential for understanding ecosystem carbon and nutrient cycling. Yet, extracting data from minirhizotron images requires intensive annotation effort. Existing annotation tools often lack flexibility and provide only a subset of the required functionality. To facilitate efficient root annotation in minirhizotrons, we present the user-friendly open source tool rhizoTrak. Methods and results rhizoTrak builds on TrakEM2 and is publically available as Fiji plugin. It uses treelines to represent branching structures in roots and assigns customizable status labels per root segment. rhizoTrak offers configuration options for visualization and various functions for root annotation mostly accessible via keyboard shortcuts. rhizoTrak allows time-series data import and particularly supports easy handling and annotation of time series images. This is facilitated via explicit temporal links (connectors) between roots which are automatically generated when copying annotations from one image to the next. rhizoTrak includes automatic consistency checks and guided procedures for resolving conflicts. It facilitates easy data exchange with other software by supporting open data formats. Conclusions rhizoTrak covers the full range of functions required for user-friendly and efficient annotation of time-series images. Its flexibility and open source nature will foster efficient data acquisition procedures in root studies using minirhizotrons.

Plant traits are poor predictors of long-term ecosystem functioning

Abstract: Earth is home to over 350,000 vascular plant species1 that differ in their traits in innumerable ways. Yet, a handful of functional traits can help explaining major differences among species in photosynthetic rate, growth rate, reproductive output and other aspects of plant performance2–6. A key challenge, coined “the Holy Grail” in ecology, is to upscale this understanding in order to predict how natural or anthropogenically driven changes in the identity and diversity of co-occurring plant species drive the functioning of ecosystems7, 8. Here, we analyze the extent to which 42 different ecosystem functions can be predicted by 41 plant traits in 78 experimentally manipulated grassland plots over 10 years. Despite the unprecedented number of traits analyzed, the average percentage of variation in ecosystem functioning that they jointly explained was only moderate (32.6%) within individual years, and even much lower (12.7%) across years. Most other studies linking ecosystem functioning to plant traits analyzed no more than six traits, and when including either only six random or the six most frequently studied traits in our analysis, the average percentage of explained variation in across-year ecosystem functioning dropped to 4.8%. Furthermore, different ecosystem functions were driven by different traits, with on average only 12.2% overlap in significant predictors. Thus, we did not find evidence for the existence of a small set of key traits able to explain variation in multiple ecosystem functions across years. Our results therefore suggest that there are strong limits in the extent to which we can predict the long-term functional consequences of the ongoing, rapid changes in the composition and diversity of plant communities that humanity is currently facing.