Effect of floristic composition and configuration on plant root mycobiota: a landscape transposition at a small scale

Fungal communities in the root endosphere are heterogeneous at fine scale. The passenger hypothesis assumes that this heterogeneity is driven by host plant distribution. Plant composition and host plant configuration should then influence root fungal assemblages. We used a large-scale experimental design of 25 mixtures of grassland plants. We sampled Brachypodium pinnatum in each mesocosm, and used amplicon mass-sequencing to analyze the endospheric mycobiota. We used plant distribution maps to assess plant species richness and evenness (heterogeneity of composition), and patch size and the degree of isolation of B. pinnatum (heterogeneity of configuration) on fungal community assembly. The Glomeromycotina community in B. pinnatum roots was not related to either floristic heterogeneity or productivity. For Ascomycota, the composition of operational taxonomic units (OTUs) was driven by plant evenness while OTU richness decreased with plant richness. For Basidiomycota, richness increased with host plant aggregation and connectivity. Plant productivity influenced Ascomycota, inducing a shift in OTU composition and decreasing evenness. Plant heterogeneity modified root mycobiota, with potential direct (i.e. host preference) and indirect (i.e. adaptations to abiotic conditions driven by plant occurrence over time) effects. Plant communities can be envisioned as microlandscapes consisting of a variety of fungal niches.

When does local spatial structure hinder competitive coexistence and reverse competitive hierarchies?

Classical theory states that if conspecifics have a greater competitive effect on individuals than heterospecifics then coexistence should occur, and ecologists have spent much effort exploring ways to generate coexistence when this condition is not met. One process that has received particular attention in the last two decades is the effect of within-species aggregation and between-species segregation caused by limited dispersal. A number of theories have emerged as to how this common spatial pattern may help maintain biodiversity, and the general conclusion that has emerged is that spatial structure should almost always help competitors to coexist. But does spatial structure really always aid biodiversity? An individual-based model based on a spatial extension to the Lotka-Volterra competition equations and its mathematical approximation are presented to determine how local spatial structure may affect communities in which there is strong niche differentiation. Two main results emerge from analyses of the models. First, intraspecific competition being greater than interspecific competition coexistence may no longer be sufficient to generate coexistence when spatial structure is strong; and the species with the highest intraspecific competition coefficient is likely to be excluded. Second, dominance hierarchies may be reversed so that a competitor may become the subordinate species when dispersal and competitive interactions occur over short spatial scales. Both results emerge because, even though a species may be globally rare, intense clumping means most interactions occur between conspecifics, and if this is very intense it may be sufficient to stop a species from invading. However, long-range dispersal may ameliorate these effects by reducing the frequency of conspecific interactions, and this is especially important when a species is rare since it is very likely to land in an area dominated by heterospecifics. These results are most relevant to sessile organisms that produce relatively few viable offspring that survive to adulthood and that have relatively weak dispersal. The conclusion is that within-species aggregation may hinder coexistence when the toughest competitor an individual is likely to face is a member of its own species.

Neighborhood effects and size-asymmetric competition in a tree plantation varying in diversity

A plantation of native trees was established in Panama in 2001 to study the relationship between biodiversity and ecosystem functioning. Five years later, mixed-species plots had experienced enhanced tree growth compared with monocultures. Searching for underlying mechanisms, we developed a neighborhood model isolating size and identity effects. We found that the size of neighbors is, by far, the largest source of variation in individual-tree diameter and height. Size-asymmetric competition appears as a structuring factor in the plantation. The relative growth rate of small trees was significantly lower than that of large trees, and their height and basal diameter were most variable. The 50 smallest trees of the plantation suffered a disproportionate amount of death, and the proportion of small trees was highest in monoculture. Increased biomass allocation to branches for trees growing in three-species plots suggests that competition for light might be taking place. Clearly, local neighborhood plays a central role in determining productivity, suggesting that scale needs to be incorporated in the theoretical development and analysis of biodiversity and ecosystem functioning.

Annual plants under cyclic disturbance regime: better understanding through model aggregation

In their application for conservation ecology, "classical" analytical models and individual-based simulation models (IBMs) both entail their specific strengths and weaknesses, either in providing a detailed and realistic representation of processes or in regard to a comprehensive model analysis. This well-known dilemma may be resolved by the combination of both approaches when tackling certain problems of conservation ecology. Following this idea, we present the complementary use of both an IBM and a matrix population model in a case study on grassland conservation management. First, we develop a spatially explicit IBM to simulate the long-term response of the annual plant Thlaspi perfoliatum (Brassicaceae), claspleaf pennycress, to different management schemes (annual mowing vs. infrequent rototilling) based on field experiments. In order to complement the simulation results by further analyses, we aggregate the IBM to a spatially nonexplicit deterministic matrix population model. Within the periodic environment created by management regimes, population dynamics are described by periodic products of annual transition matrices. Such periodic matrix products provide a very conclusive framework to study the responses of species to different management return intervals. Thus, using tools of matrix model analysis (e.g., loop analysis), we can both identify dormancy within the age-structured seed bank as the pivotal strategy for persistence under cyclic disturbance regimes and reveal crucial thresholds in some less certain parameters. Results of matrix model analyses are therefore successfully tested by comparing their results to the respective IBM simulations. Their implications for an enhanced scientific basis for management decisions are discussed as well as some general benefits and limitations of the use of aggregating modeling approaches in conservation.

Analysis of neighborhood dynamics of forest ecosystems using likelihood methods and modeling

Advances in computing power in the past 20 years have led to a proliferation of spatially explicit, individual-based models of population and ecosystem dynamics. In forest ecosystems, the individual-based models encapsulate an emerging theory of "neighborhood" dynamics, in which fine-scale spatial interactions regulate the demography of component tree species. The spatial distribution of component species, in turn, regulates spatial variation in a whole host of community and ecosystem properties, with subsequent feedbacks on component species. The development of these models has been facilitated by development of new methods of analysis of field data, in which critical demographic rates and ecosystem processes are analyzed in terms of the spatial distributions of neighboring trees and physical environmental factors. The analyses are based on likelihood methods and information theory, and they allow a tight linkage between the models and explicit parameterization of the models from field data. Maximum likelihood methods have a long history of use for point and interval estimation in statistics. In contrast, likelihood principles have only more gradually emerged in ecology as the foundation for an alternative to traditional hypothesis testing. The alternative framework stresses the process of identifying and selecting among competing models, or in the simplest case, among competing point estimates of a parameter of a model. There are four general steps involved in a likelihood analysis: (1) model specification, (2) parameter estimation using maximum likelihood methods, (3) model comparison, and (4) model evaluation. Our goal in this paper is to review recent developments in the use of likelihood methods and modeling for the analysis of neighborhood processes in forest ecosystems. We will focus on a single class of processes, seed dispersal and seedling dispersion, because recent papers provide compelling evidence of the potential power of the approach, and illustrate some of the statistical challenges in applying the methods.

Local Spatial Structure and Predator‐Prey Dynamics: Counterintuitive Effects of Prey Enrichment

The Lotka-Volterra predator-prey model with prey density dependence shows the final prey density to be independent of its vital rates. This result assumes the community to be well mixed so that encounters between predators and prey occur as a product of the landscape densities, yet empirical evidence suggests that over small spatial scales this may not be the normal pattern. Starting from an individual-based model with neighborhood interactions and movements, a deterministic approximation is derived, and the effect of local spatial structure on equilibrium densities is investigated. Incorporating local movements and local interactions has important consequences for the community dynamics. Now the final prey density is very much dependent on its birth, death, and movement rates and in ways that seem counterintuitive. Increasing prey fecundity or mobility and decreasing the coefficient of competition can all lead to decreases in the final density of prey if the predator is also relatively immobile. However, analysis of the deterministic approximation makes the mechanism for these results clear; each of these changes subtly alters the emergent spatial structure, leading to an increase in the predator-prey spatial covariance at short distances and hence to a higher predation pressure on the prey.