Using a multi-trait approach to manipulate plant functional diversity in a biodiversity-ecosystem function experiment.
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ABSTRACT:
SUBMITTER: Schittko C
PROVIDER: S-EPMC4045913 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Understanding the relationship between biodiversity and ecosystem functioning has been a core ecological research topic over the last decades. Although a key hypothesis is that the diversity of functional traits determines ecosystem functioning, we do not know how much trait diversity is needed to maintain multiple ecosystem functions simultaneously (multifunctionality). Here, we uncovered a scaling relationship between the abundance distribution of two key plant functional traits (specific leaf area, maximum plant height) and multifunctionality in 124 dryland plant communities spread over all continents except Antarctica. For each trait, we found a strong empirical relationship between the skewness and the kurtosis of the trait distributions that cannot be explained by chance. This relationship predicted a strikingly high trait diversity within dryland plant communities, which was associated with a local maximization of multifunctionality. Skewness and kurtosis had a much stronger impact on multifunctionality than other important multifunctionality drivers such as species richness and aridity. The scaling relationship identified here quantifies how much trait diversity is required to maximize multifunctionality locally. Trait distributions can be used to predict the functional consequences of biodiversity loss in terrestrial ecosystems.
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Project description:Diversity loss has been shown to change the soil community; however, little is known about long-term consequences and underlying mechanisms. Here, we investigated how nematode communities are affected by plant species richness and whether this is driven by resource quantity or quality in 15-year-old plant communities of a long-term grassland biodiversity experiment. We extracted nematodes from 93 experimental plots differing in plant species richness, and measured above- and belowground plant biomass production and soil organic carbon concentrations (Corg) as proxies for resource quantity, as well as C/Nleaf ratio and specific root length (SRL) as proxies for resource quality. We found that nematode community composition and diversity significantly differed among plant species richness levels. This was mostly due to positive plant diversity effects on the abundance and genus richness of bacterial-feeding, omnivorous, and predatory nematodes, which benefited from higher shoot mass and soil Corg in species-rich plant communities, suggesting control via resource quantity. In contrast, plant-feeding nematodes were negatively influenced by shoot mass, probably due to higher top-down control by predators, and were positively related to SRL and C/Nleaf, indicating control via resource quality. The decrease of the grazing pressure ratio (plant feeders per root mass) with plant species richness indicated a higher accumulation of plant-feeding nematodes in species-poor plant communities. Our results, therefore, support the hypothesis that soil-borne pathogens accumulate in low-diversity communities over time, while soil mutualists (bacterial-feeding, omnivorous, predatory nematodes) increase in abundance and richness in high-diversity plant communities, which may contribute to the widely-observed positive plant diversity-productivity relationship.
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Project description:In ecology, biodiversity-ecosystem functioning (BEF) research has seen a shift in perspective from taxonomy to function in the last two decades, with successful application of trait-based approaches. This shift offers opportunities for a deeper mechanistic understanding of the role of biodiversity in maintaining multiple ecosystem processes and services. In this paper, we highlight studies that have focused on BEF of microbial communities with an emphasis on integrating trait-based approaches to microbial ecology. In doing so, we explore some of the inherent challenges and opportunities of understanding BEF using microbial systems. For example, microbial biologists characterize communities using gene phylogenies that are often unable to resolve functional traits. Additionally, experimental designs of existing microbial BEF studies are often inadequate to unravel BEF relationships. We argue that combining eco-physiological studies with contemporary molecular tools in a trait-based framework can reinforce our ability to link microbial diversity to ecosystem processes. We conclude that such trait-based approaches are a promising framework to increase the understanding of microbial BEF relationships and thus generating systematic principles in microbial ecology and more generally ecology.
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Project description:The functional diversity of a community can influence ecosystem functioning and reflects assembly processes. The large number of disparate metrics used to quantify functional diversity reflects the range of attributes underlying this concept, generally summarized as functional richness, functional evenness, and functional divergence. However, in practice, we know very little about which attributes drive which ecosystem functions, due to a lack of field-based tests. Here we test the association between eight leading functional diversity metrics (Rao's Q, FD, FDis, FEve, FDiv, convex hull volume, and species and functional group richness) that emphasize different attributes of functional diversity, plus 11 extensions of these existing metrics that incorporate heterogeneous species abundances and trait variation. We assess the relationships among these metrics and compare their performances for predicting three key ecosystem functions (above- and belowground biomass and light capture) within a long-term grassland biodiversity experiment. Many metrics were highly correlated, although unique information was captured in FEve, FDiv, and dendrogram-based measures (FD) that were adjusted by abundance. FD adjusted by abundance outperformed all other metrics in predicting both above- and belowground biomass, although several others also performed well (e.g. Rao's Q, FDis, FDiv). More generally, trait-based richness metrics and hybrid metrics incorporating multiple diversity attributes outperformed evenness metrics and single-attribute metrics, results that were not changed when combinations of metrics were explored. For light capture, species richness alone was the best predictor, suggesting that traits for canopy architecture would be necessary to improve predictions. Our study provides a comprehensive test linking different attributes of functional diversity with ecosystem function for a grassland system.
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Project description:Biodiversity losses are a major driver of global changes in ecosystem functioning. While most studies of the relationship between biodiversity and ecosystem functioning have examined randomized species losses, trait-based filtering associated with species-specific vulnerability to drivers of diversity loss can strongly influence how ecosystem functioning responds to declining biodiversity. Moreover, the responses of ecosystem functioning to diversity loss may be mediated by environmental variability interacting with the suite of traits remaining in depauperate communities. We do not yet understand how communities resulting from realistic diversity losses (filtered by response traits) influence ecosystem functioning (via effect traits of the remaining community), especially under variable environmental conditions. Here, we directly test how realistic and randomized plant diversity losses influence productivity and invasion resistance across multiple years in a California grassland. Compared with communities based on randomized diversity losses, communities resulting from realistic (drought-driven) species losses had higher invasion resistance under climatic conditions that matched the trait-based filtering they experienced. However, productivity declined more with realistic than with randomized species losses across all years, regardless of climatic conditions. Functional response traits aligned with effect traits for productivity but not for invasion resistance. Our findings illustrate that the effects of biodiversity losses depend not only on the identities of lost species but also on how the traits of remaining species interact with varying environmental conditions. Understanding the consequences of biodiversity change requires studies that evaluate trait-mediated effects of species losses and incorporate the increasingly variable climatic conditions that future communities are expected to experience.
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Project description:BackgroundTwo decades of research showing that increasing plant diversity results in greater community productivity has been predicated on greater functional diversity allowing access to more of the total available resources. Thus, understanding phenotypic attributes that allow species to partition resources is fundamentally important to explaining diversity-productivity relationships.Methodology/principal findingsHere we use data from a long-term experiment (Cedar Creek, MN) and compare the extent to which productivity is explained by seven types of community metrics of functional variation: 1) species richness, 2) variation in 10 individual traits, 3) functional group richness, 4) a distance-based measure of functional diversity, 5) a hierarchical multivariate clustering method, 6) a nonmetric multidimensional scaling approach, and 7) a phylogenetic diversity measure, summing phylogenetic branch lengths connecting community members together and may be a surrogate for ecological differences. Although most of these diversity measures provided significant explanations of variation in productivity, the presence of a nitrogen fixer and phylogenetic diversity were the two best explanatory variables. Further, a statistical model that included the presence of a nitrogen fixer, seed weight and phylogenetic diversity was a better explanation of community productivity than other models.ConclusionsEvolutionary relationships among species appear to explain patterns of grassland productivity. Further, these results reveal that functional differences among species involve a complex suite of traits and that perhaps phylogenetic relationships provide a better measure of the diversity among species that contributes to productivity than individual or small groups of traits.
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Project description:Classical biogeographical observations suggest that ecosystems are strongly shaped by climatic constraints in terms of their structure and function. On the other hand, vegetation function feeds back on the climate system via biosphere-atmosphere exchange of matter and energy. Ecosystem-level observations of this exchange reveal very large functional biogeographical variation of climate-relevant ecosystem functional properties related to carbon and water cycles. This variation is explained insufficiently by climate control and a classical plant functional type classification approach. For example, correlations between seasonal carbon-use efficiency and climate or environmental variables remain below 0.6, leaving almost 70% of variance unexplained. We suggest that a substantial part of this unexplained variation of ecosystem functional properties is related to variations in plant and microbial traits. Therefore, to progress with global functional biogeography, we should seek to understand the link between organismic traits and flux-derived ecosystem properties at ecosystem observation sites and the spatial variation of vegetation traits given geoecological covariates. This understanding can be fostered by synergistic use of both data-driven and theory-driven ecological as well as biophysical approaches.
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Project description:Declines in biodiversity have prompted concern over the consequences of species loss for the goods and services provided by natural ecosystems. However, relatively few studies have evaluated the functional consequences of realistic, nonrandom changes in biodiversity. Instead, most designs have used randomly selected assemblages from a local species pool to construct diversity gradients. It is therefore difficult, based on current evidence, to predict the functional consequences of realistic declines in biodiversity. In this study, we used tide pool microcosms to demonstrate that the effects of real-world changes in biodiversity may be very different from those of random diversity changes. Specifically, we measured the relationship between the diversity of a seaweed assemblage and its ability to use nitrogen, a key limiting nutrient in nearshore marine systems. We quantified nitrogen uptake using both experimental and model seaweed assemblages and found that natural increases in diversity resulted in enhanced rates of nitrogen use, whereas random diversity changes had no effect on nitrogen uptake. Our results suggest that understanding the real-world consequences of declining biodiversity will require addressing changes in species performance along natural diversity gradients and understanding the relationships between species' susceptibility to loss and their contributions to ecosystem functioning.
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