One of ecology's grand challenges is developing general rules to explain and predict highly complex systems. Understanding and predicting ecological processes from species' traits has been considered a 'Holy Grail' in ecology. Plant functional traits are increasingly being used to develop mechanistic models that can predict how ecological communities will respond to abiotic and biotic perturbations and how species will affect ecosystem function and services in a rapidly changing world; however, significant challenges remain. In this review, we highlight recent work and outstanding questions in three areas: (i) selecting relevant traits; (ii) describing intraspecific trait variation and incorporating this variation into models; and (iii) scaling trait data to community- and ecosystem-level processes. Over the past decade, there have been significant advances in the characterization of plant strategies based on traits and trait relationships, and the integration of traits into multivariate indices and models of community and ecosystem function. However, the utility of trait-based approaches in ecology will benefit from efforts that demonstrate how these traits and indices influence organismal, community, and ecosystem processes across vegetation types, which may be achieved through meta-analysis and enhancement of trait databases. Additionally, intraspecific trait variation and species interactions need to be incorporated into predictive models using tools such as Bayesian hierarchical modelling. Finally, existing models linking traits to community and ecosystem processes need to be empirically tested for their applicability to be realized.
Deciphering the mechanisms that link biodiversity with ecosystem functions is critical to understanding the consequences of changes in biodiversity. The hypothesis that complementarity and selection effects drive relationships between biodiversity and ecosystem functions is well accepted, and an approach to statistically untangle the relative importance of these effects has been widely applied. In contrast, empirical demonstrations of the biological mechanisms that underlie these relationships remain rare. Here, on the basis of a field experiment with young trees, we provide evidence that one form of complementarity in plant communities-complementarity among crowns in canopy space-is a mechanism, related to light interception and use, that links biodiversity with ecosystem productivity. Stem biomass overyielding increased sharply in mixtures with greater crown complementarity. Inherent differences among species in crown architecture led to greater crown complementarity in functionally diverse species mixtures. Intraspecific variation, specifically neighbourhood-driven plasticity in crowns, further modified spatial complementarity and strengthened the positive relationship with overyielding-crown plasticity and inherent interspecific differences contributed near equally in explaining patterns of overyielding. We posit that crown complementarity is an important mechanism that may contribute to diversity-enhanced productivity in forests.
Two main effects are proposed to explain biodiversity-ecosystem functioning relationships: niche complementarity and selection effects. Both can be functionally defined using the functional diversity (FD) and functional identity (FI) of the community respectively. Herein, we present results from the first tree diversity experiment that separated the effect of selection from that of complementarity by varying community composition in high-density plots along a gradient of FD, independent of species richness and testing for the effects of FD and community weighted means of traits (a proxy for FI) on stem biomass increment (a proxy for productivity). After 4 years of growth, most mixtures did not differ in productivity from the averages of their respective monocultures, but some did overyield significantly. Those positive diversity effects resulted mostly from selection effects, primarily driven by fast-growing deciduous species and associated traits. Net diversity effect did not increase with time over 4 years.
Through litter decomposition enormous amounts of carbon is emitted to the atmosphere. Numerous large-scale decomposition experiments have been conducted focusing on this fundamental soil process in order to understand the controls on the terrestrial carbon transfer to the atmosphere. However, previous studies were mostly based on site-specific litter and methodologies, adding major uncertainty to syntheses, comparisons and meta-analyses across different experiments and sites. In the TeaComposition initiative, the potential litter decomposition is investigated by using standardized substrates (Rooibos and Green tea) for comparison of litter mass loss at 336 sites (ranging from -9 to +26 °C MAT and from 60 to 3113 mm MAP) across different ecosystems. In this study we tested the effect of climate (temperature and moisture), litter type and land-use on early stage decomposition (3 months) across nine biomes. We show that litter quality was the predominant controlling factor in early stage litter decomposition, which explained about 65% of the variability in litter decomposition at a global scale. The effect of climate, on the other hand, was not litter specific and explained <0.5% of the variation for Green tea and 5% for Rooibos tea, and was of significance only under unfavorable decomposition conditions (i.e. xeric versus mesic environments). When the data were aggregated at the biome scale, climate played a significant role on decomposition of both litter types (explaining 64% of the variation for Green tea and 72% for Rooibos tea). No significant effect of land-use on early stage litter decomposition was noted within the temperate biome. Our results indicate that multiple drivers are affecting early stage litter mass loss with litter quality being dominant. In order to be able to quantify the relative importance of the different drivers over time, long-term studies combined with experimental trials are needed.
Exploring the link between above- and belowground biodiversity has been a major theme of recent ecological research, due in large part to the increasingly well-recognized role that soil microorganisms play in driving plant community processes. In this study, we utilized a field-based tree experiment in Minnesota, USA, to assess the effect of changes in plant species richness and phylogenetic diversity on the richness and composition of both ectomycorrhizal and saprotrophic fungal communities. We found that ectomycorrhizal fungal species richness was significantly positively influenced by increasing plant phylogenetic diversity, while saprotrophic fungal species richness was significantly affected by plant leaf nitrogen content, specific root length and standing biomass. The increasing ectomycorrhizal fungal richness associated with increasing plant phylogenetic diversity was driven by the combined presence of ectomycorrhizal fungal specialists in plots with both gymnosperm and angiosperm hosts. Although the species composition of both the ectomycorrhizal and saprotrophic fungal communities changed significantly in response to changes in plant species composition, the effect was much greater for ectomycorrhizal fungi. In addition, ectomycorrhizal but not saprotrophic fungal species composition was significantly influenced by both plant phylum (angiosperm, gymnosperm, both) and origin (Europe, America, both). The phylum effect was caused by differences in ectomycorrhizal fungal community composition, while the origin effect was attributable to differences in community heterogeneity. Taken together, this study emphasizes that plant-associated effects on soil fungal communities are largely guild-specific and provides a mechanistic basis for the positive link between plant phylogenetic diversity and ectomycorrhizal fungal richness.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.