Fruits, Frugivores, and the Evolution of Phytochemical Diversity

Plants produce an enormous diversity of secondary metabolites, but the evolutionary mechanisms that maintain this diversity are still unclear. The interaction diversity hypothesis suggests that complex chemical phenotypes are maintained because different metabolites benefit plants in different pairwise interactions with a diversity of other organisms. In this synthesis, we extend the interaction diversity hypothesis to consider that fruits, as potential hotspots of interactions with both antagonists and mutualists, are likely important incubators of phytochemical diversity. We provide a case study focused on the Neotropical shrub Piper reticulatum that demonstrates: 1) secondary metabolites in fruits have complex and cascading effects for shaping the outcome of both mutualistic and antagonistic fruit–frugivore interactions, and; 2) fruits can harbor substantially higher levels of phytochemical diversity than leaves, even though leaves have been the primary focus of plant chemical ecology research for decades. We then suggest a number of research priorities for integrating chemical ecology with fruit–frugivore interaction research and make specific, testable predictions for patterns that should emerge if fruit interaction diversity has helped shape phytochemical diversity. Testing these predictions in a range of systems will provide new insight into the mechanisms driving frugivory and seed dispersal and shape an improved, whole-plant perspective on plant chemical trait evolution

Scaling from individual trees to forests in an Earth system modeling framework using a mathematically tractable model of height-structured competition

The long-term and large-scale dynamics of ecosystems are in large part determined by the performances of individual plants in competition with one another for light, water, and nutrients. Woody biomass, a pool of carbon (C) larger than 50% of atmospheric CO2, exists because of height-structured competition for light. However, most of the current Earth system models that predict climate change and C cycle feedbacks lack both a mechanistic formulation for height-structured competition for light and an explicit scaling from individual plants to the globe. In this study, we incorporate height-structured competition for light, competition for water, and explicit scaling from individuals to ecosystems into the land model version 3 (LM3) currently used in the Earth system models developed by the Geophysical Fluid Dynamics Laboratory (GFDL). The height-structured formulation is based on the perfect plasticity approximation (PPA), which has been shown to accurately scale from individual-level plant competition for light, water, and nutrients to the dynamics of whole communities. Because of the tractability of the PPA, the coupled LM3-PPA model is able to include a large number of phenomena across a range of spatial and temporal scales and still retain computational tractability, as well as close linkages to mathematically tractable forms of the model. We test a range of predictions against data from temperate broadleaved forests in the northern USA. The results show the model predictions agree with diurnal and annual C fluxes, growth rates of individual trees in the canopy and understory, tree size distributions, and species-level population dynamics during succession. We also show how the competitively optimal allocation strategy - the strategy that can competitively exclude all others - shifts as a function of the atmospheric CO2 concentration. This strategy is referred to as an evolutionarily stable strategy (ESS) in the ecological literature and is typically not the same as a productivity-or growth-maximizing strategy. Model simulations predict that C sinks caused by CO2 fertilization in forests limited by light and water will be down-regulated if allocation tracks changes in the competitive optimum. The implementation of the model in this paper is for temperate broadleaved forest trees, but the formulation of the model is general. It can be expanded to include other growth forms and physiologies simply by altering parameter values

Evolution of Competitive Ability: An Adaptation Speed vs. Accuracy Tradeoff Rooted in Gene Network Size

Ecologists have increasingly come to understand that evolutionary change on short time-scales can alter ecological dynamics (and vice-versa), and this idea is being incorporated into community ecology research programs. Previous research has suggested that the size and topology of the gene network underlying a quantitative trait should constrain or facilitate adaptation and thereby alter population dynamics. Here, I consider a scenario in which two species with different genetic architectures compete and evolve in fluctuating environments. An important trade-off emerges between adaptive accuracy and adaptive speed, driven by the size of the gene network underlying the ecologically-critical trait and the rate of environmental change. Smaller, scale-free networks confer a competitive advantage in rapidly-changing environments, but larger networks permit increased adaptive accuracy when environmental change is sufficiently slow to allow a species time to adapt. As the differences in network characteristics increase, the time-to-resolution of competition decreases. These results augment and refine previous conclusions about the ecological implications of the genetic architecture of quantitative traits, emphasizing a role of adaptive accuracy. Along with previous work, in particular that considering the role of gene network connectivity, these results provide a set of expectations for what we may observe as the field of ecological genomics develops

Plant Trait Diversity Buffers Variability in Denitrification Potential over Changes in Season and Soil Conditions

BACKGROUND: Denitrification is an important ecosystem service that removes nitrogen (N) from N-polluted watersheds, buffering soil, stream, and river water quality from excess N by returning N to the atmosphere before it reaches lakes or oceans and leads to eutrophication. The denitrification enzyme activity (DEA) assay is widely used for measuring denitrification potential. Because DEA is a function of enzyme levels in soils, most ecologists studying denitrification have assumed that DEA is less sensitive to ambient levels of nitrate (NO(3)(-)) and soil carbon and thus, less variable over time than field measurements. In addition, plant diversity has been shown to have strong effects on microbial communities and belowground processes and could potentially alter the functional capacity of denitrifiers. Here, we examined three questions: (1) Does DEA vary through the growing season? (2) If so, can we predict DEA variability with environmental variables? (3) Does plant functional diversity affect DEA variability? METHODOLOGY/PRINCIPAL FINDINGS: The study site is a restored wetland in North Carolina, US with native wetland herbs planted in monocultures or mixes of four or eight species. We found that denitrification potentials for soils collected in July 2006 were significantly greater than for soils collected in May and late August 2006 (p<0.0001). Similarly, microbial biomass standardized DEA rates were significantly greater in July than May and August (p<0.0001). Of the soil variables measured--soil moisture, organic matter, total inorganic nitrogen, and microbial biomass--none consistently explained the pattern observed in DEA through time. There was no significant relationship between DEA and plant species richness or functional diversity. However, the seasonal variance in microbial biomass standardized DEA rates was significantly inversely related to plant species functional diversity (p<0.01). CONCLUSIONS/SIGNIFICANCE: These findings suggest that higher plant functional diversity may support a more constant level of DEA through time, buffering the ecosystem from changes in season and soil conditions

Biomass and morphology of fine roots in temperate broad-leaved forests differing in tree species diversity: is there evidence of below-ground overyielding?

Biodiversity effects on ecosystem functioning in forests have only recently attracted increasing attention. The vast majority of studies in forests have focused on above-ground responses to differences in tree species diversity, while systematic analyses of the effects of biodiversity on root systems are virtually non-existent. By investigating the fine root systems in 12 temperate deciduous forest stands in Central Europe, we tested the hypotheses that (1) stand fine root biomass increases with tree diversity, and (2) ‘below-ground overyielding’ of species-rich stands in terms of fine root biomass is the consequence of spatial niche segregation of the roots of different species. The selected stands represent a gradient in tree species diversity on similar bedrock from almost pure beech forests to medium-diverse forests built by beech, ash, and lime, and highly-diverse stands dominated by beech, ash, lime, maple, and hornbeam. We investigated fine root biomass and necromass at 24 profiles per stand and analyzed species differences in fine root morphology by microscopic analysis. Fine root biomass ranged from 440 to 480 g m−2 in the species-poor to species-rich stands, with 63–77% being concentrated in the upper 20 cm of the soil. In contradiction to our two hypotheses, the differences in tree species diversity affected neither stand fine root biomass nor vertical root distribution patterns. Fine root morphology showed marked distinctions between species, but these root morphological differences did not lead to significant differences in fine root surface area or root tip number on a stand area basis. Moreover, differences in species composition of the stands did not alter fine root morphology of the species. We conclude that ‘below-ground overyielding’ in terms of fine root biomass does not occur in the species-rich stands, which is most likely caused by the absence of significant spatial segregation of the root systems of these late-successional species

Scaling from individual trees to forests in an Earth system modeling framework using a mathematically tractable model of height-structured competition

The long-term and large-scale dynamics of ecosystems are in large part determined by the performances of individual plants in competition with one another for light, water, and nutrients. Woody biomass, a pool of carbon (C) larger than 50 % of atmospheric CO2, exists because of height-structured competition for light. However, most of the current Earth system models that predict climate change and C cycle feedbacks lack both a mechanistic formulation for height-structured competition for light and an explicit scaling from individual plants to the globe. In this study, we incorporate height-structured competition for light, competition for water, and explicit scaling from individuals to ecosystems into the land model version 3 (LM3) currently used in the Earth system models developed by the Geophysical Fluid Dynamics Laboratory (GFDL). The height-structured formulation is based on the perfect plasticity approximation (PPA), which has been shown to accurately scale from individual-level plant competition for light, water, and nutrients to the dynamics of whole communities. Because of the tractability of the PPA, the coupled LM3-PPA model is able to include a large number of phenomena across a range of spatial and temporal scales and still retain computational tractability, as well as close linkages to mathematically tractable forms of the model. We test a range of predictions against data from temperate broadleaved forests in the northern USA. The results show the model predictions agree with diurnal and annual C fluxes, growth rates of individual trees in the canopy and understory, tree size distributions, and species-level population dynamics during succession. We also show how the competitively optimal allocation strategy – the strategy that can competitively exclude all others – shifts as a function of the atmospheric CO2 concentration. This strategy is referred to as an evolutionarily stable strategy (ESS) in the ecological literature and is typically not the same as a productivity or growth-maximizing strategy. Model simulations predict that C sinks caused by CO2 fertilization in forests limited by light and water will be down-regulated if allocation tracks changes in the competitive optimum. The implementation of the model in this paper is for temperate broadleaved forest trees, but the formulation of the model is general. It can be expanded to include other growth forms and physiologies simply by altering parameter values