Search for: All records

ABSTRACT Many animals contain a species-rich and diverse gut microbiota that likely contributes to several host-supportive services that include diet processing and nutrient provisioning. Loss of microbiome taxa and their associated metabolic functions as result of perturbations may result in loss of microbiome-level services and reduction of metabolic capacity. If metabolic functions are shared by multiple taxa (i.e., functional redundancy), including deeply divergent lineages, then the impact of taxon/function losses may be dampened. We examined to what degree alterations in phylotype diversity impact microbiome-level metabolic capacity. Feeding two nutritionally imbalanced diets to omnivorousPeriplaneta americanaover 8 weeks reduced the diversity of their phylotype-rich gut microbiomes by ~25% based on 16S rRNA gene amplicon sequencing, yet PICRUSt2-inferred metabolic pathway richness was largely unaffected due to their being polyphyletic. We concluded that the nonlinearity between taxon and metabolic functional losses is due to microbiome members sharing many well-characterized metabolic functions, with lineages remaining after perturbation potentially being capable of preventing microbiome “service outages” due to functional redundancy. IMPORTANCEDiet can affect gut microbiome taxonomic composition and diversity, but its impacts on community-level functional capabilities are less clear. Host health and fitness are increasingly being linked to microbiome composition and further modeling of the relationship between microbiome taxonomic and metabolic functional capability is needed to inform these linkages. Invertebrate animal models like the omnivorous American cockroach are ideal for this inquiry because they are amenable to various diets and provide high replicates per treatment at low costs and thus enabling rigorous statistical analyses and hypothesis testing. Microbiome taxonomic composition is diet-labile and diversity was reduced after feeding on unbalanced diets (i.e., post-treatment), but the predicted functional capacities of the post-treatment microbiomes were less affected likely due to the resilience of several abundant taxa surviving the perturbation as well as many metabolic functions being shared by several taxa. These results suggest that both taxonomic and functional profiles should be considered when attempting to infer how perturbations are altering gut microbiome services and possible host outcomes. 

Seed dispersal, or the movement of diaspores away from the parent location, is a multiscale, multipartner process that depends on the interaction of plant life history with vector movement and the environment. Seed dispersal underpins many important plant ecological and evolutionary processes such as gene flow, population dynamics, range expansion, and diversity. We review exciting new directions that the field of seed dispersal ecology and evolution has taken over the past 40 years. We provide an overview of the ultimate causes of dispersal and the consequences of this important process for plant population and community dynamics. We also discuss several emergent unifying frameworks that are being used to study dispersal and describe how they can be integrated to provide a more mechanistic understanding of dispersal. 

Abstract Premise The specialized metabolites of plants are recognized as key chemical traits in mediating the ecology and evolution of sundry plant–biotic interactions, from pollination to seed predation. Intra‐ and interspecific patterns of specialized metabolite diversity have been studied extensively in leaves, but the diverse biotic interactions that contribute to specialized metabolite diversity encompass all plant organs. Focusing on two species of Psychotria shrubs, we investigated and compared patterns of specialized metabolite diversity in leaves and fruit with respect to each organ's diversity of biotic interactions. Methods To evaluate associations between biotic interaction diversity and specialized metabolite diversity, we combined UPLC‐MS metabolomic analysis of foliar and fruit specialized metabolites with existing surveys of leaf‐ and fruit‐centered biotic interactions. We compared patterns of specialized metabolite richness and variance among vegetative and reproductive tissues, among plants, and between species. Results In our study system, leaves interact with a far larger number of consumer species than do fruit, while fruit‐centric interactions are more ecologically diverse in that they involve antagonistic and mutualistic consumers. This aspect of fruit‐centric interactions was reflected in specialized metabolite richness—leaves contained more than fruit, while each organ contained over 200 organ‐specific specialized metabolites. Within each species, leaf‐ and fruit‐specialized metabolite composition varied independently of one another across individual plants. Contrasts in specialized metabolite composition were stronger between organs than between species. Conclusions As ecologically disparate plant organs with organ‐specific specialized metabolite traits, leaves and fruit can each contribute to the tremendous overall diversity of plant specialized metabolites. 

Abstract Mounting evidence suggests that plant–soil feedbacks (PSF) may determine plant community structure. However, we still have a poor understanding of how predictions from short‐term PSF experiments compare with outcomes of long‐term field experiments involving competing plants. We conducted a reciprocal greenhouse experiment to examine how the growth of prairie grass species depended on the soil communities cultured by conspecific or heterospecific plant species in the field. The source soil came from monocultures in a long‐term competition experiment (LTCE; Cedar Creek Ecosystem Science Reserve, MN, USA). Within the LTCE, six species of perennial prairie grasses were grown in monocultures or in eight pairwise competition plots for 12 years under conditions of low or high soil nitrogen availability. In six cases, one species clearly excluded the other; in two cases, the pair appeared to coexist. In year 15, we gathered soil from all 12 soil types (monocultures of six species by two nitrogen levels) and grew seedlings of all six species in each soil type for 7 weeks. Using biomass estimates from this greenhouse experiment, we predicted coexistence or competitive exclusion using pairwise PSFs, as derived by Bever and colleagues, and compared model predictions to observed outcomes within the LTCE. Pairwise PSFs among the species pairs ranged from negative, which is predicted to promote coexistence, to positive, which is predicted to promote competitive exclusion. However, these short‐term PSF predictions bore no systematic resemblance to the actual outcomes of competition observed in the LTCE. Other forces may have more strongly influenced the competitive interactions or critical assumptions that underlie the PSF predictions may not have been met. Importantly, the pairwise PSF score derived by Bever et al. is only valid when the two species exhibit an internal equilibrium, corresponding to the Lotka–Volterra competition outcomes of stable coexistence and founder control. Predicting the other two scenarios, competitive exclusion by either species irrespective of initial conditions, requires measuring biomass in uncultured soil, which is methodologically challenging. Subject to several caveats that we discuss, our results call into question whether long‐term competitive outcomes in the field can be predicted from the results of short‐term PSF experiments. 

Abstract Dispersal and fecundity are two fundamental traits underlying the spread of populations. Using integral difference equation models, we examine how individual variation in these fundamental traits and the heritability of these traits influence rates of spatial spread of populations along a one-dimensional transect. Using a mixture of analytic and numerical methods, we show that individual variation in dispersal rates increases spread rates and the more heritable this variation, the greater the increase. In contrast, individual variation in lifetime fecundity only increases spread rates when some of this variation is heritable. The highest increases in spread rates occur when variation in dispersal positively co-varies with fecundity. Our results highlight the importance of estimating individual variation in dispersal rates, dispersal syndromes in which fecundity and dispersal co-vary positively and heritability of these traits to predict population rates of spatial spread. 

Abstract Despite the importance of seed dispersal as a driving process behind plant community assembly, our understanding of the role of seed dispersal in plant population persistence and spread remains incomplete. As a result, our ability to predict the effects of global change on plant populations is hampered. We need to better understand the fundamental link between seed dispersal and population dynamics in order to make predictive generalizations across species and systems, to better understand plant community structure and function, and to make appropriate conservation and management responses related to seed dispersal. To tackle these important knowledge gaps, we established the CoDisperse Network and convened an interdisciplinary, NSF-sponsored Seed Dispersal Workshop in 2016, during which we explored the role of seed dispersal in plant population dynamics (NSF DEB Award # 1548194). In this Special Issue, we consider the current state of seed dispersal ecology and identify the following collaborative research needs: (i) the development of a mechanistic understanding of the movement process influencing dispersal of seeds; (ii) improved quantification of the relative influence of seed dispersal on plant fitness compared to processes occurring at other life history stages; (iii) an ability to scale from individual plants to ecosystems to quantify the influence of dispersal on ecosystem function; and (iv) the incorporation of seed dispersal ecology into conservation and management strategies. 

Abstract There is growing realization that intraspecific variation in seed dispersal can have important ecological and evolutionary consequences. However, we do not have a good understanding of the drivers or causes of intraspecific variation in dispersal, how strong an effect these drivers have, and how widespread they are across dispersal modes. As a first step to developing a better understanding, we present a broad, but not exhaustive, review of what is known about the drivers of intraspecific variation in seed dispersal, and what remains uncertain. We start by decomposing ‘drivers of intraspecific variation in seed dispersal’ into intrinsic drivers (i.e. variation in traits of individual plants) and extrinsic drivers (i.e. variation in ecological context). For intrinsic traits, we further decompose intraspecific variation into variation among individuals and variation of trait values within individuals. We then review our understanding of the major intrinsic and extrinsic drivers of intraspecific variation in seed dispersal, with an emphasis on variation among individuals. Crop size is the best-supported and best-understood intrinsic driver of variation across dispersal modes; overall, more seeds are dispersed as more seeds are produced, even in cases where per seed dispersal rates decline. Fruit/seed size is the second most widely studied intrinsic driver, and is also relevant to a broad range of seed dispersal modes. Remaining intrinsic drivers are poorly understood, and range from effects that are probably widespread, such as plant height, to drivers that are most likely sporadic, such as fruit or seed colour polymorphism. Primary extrinsic drivers of variation in seed dispersal include local environmental conditions and habitat structure. Finally, we present a selection of outstanding questions as a starting point to advance our understanding of individual variation in seed dispersal. 

Abstract The distribution and abundance of plants across the world depends in part on their ability to move, which is commonly characterized by a dispersal kernel. For seeds, the total dispersal kernel (TDK) describes the combined influence of all primary, secondary and higher-order dispersal vectors on the overall dispersal kernel for a plant individual, population, species or community. Understanding the role of each vector within the TDK, and their combined influence on the TDK, is critically important for being able to predict plant responses to a changing biotic or abiotic environment. In addition, fully characterizing the TDK by including all vectors may affect predictions of population spread. Here, we review existing research on the TDK and discuss advances in empirical, conceptual modelling and statistical approaches that will facilitate broader application. The concept is simple, but few examples of well-characterized TDKs exist. We find that significant empirical challenges exist, as many studies do not account for all dispersal vectors (e.g. gravity, higher-order dispersal vectors), inadequately measure or estimate long-distance dispersal resulting from multiple vectors and/or neglect spatial heterogeneity and context dependence. Existing mathematical and conceptual modelling approaches and statistical methods allow fitting individual dispersal kernels and combining them to form a TDK; these will perform best if robust prior information is available. We recommend a modelling cycle to parameterize TDKs, where empirical data inform models, which in turn inform additional data collection. Finally, we recommend that the TDK concept be extended to account for not only where seeds land, but also how that location affects the likelihood of establishing and producing a reproductive adult, i.e. the total effective dispersal kernel.