Biology subjects

Mayfield, M. M.

Publications and source records attributed to Mayfield, M. M..

9 recordsLinked to original sources

bioRxiv2025

Neighbor density-dependent facilitation promotescoexistence and internal oscillation

The ability of species to form diverse communities is not fully understood. Species are known to interact in various ways with their neighborhood. Despite this, common models of species coexistence assume that per capita interactions are constant and competitive, even as the environment changes. In this study, we investigate how neighbor density-dependent variation in the strength and sign of species interactions changes species and community dynamics. We show that by including these sources of variation, predictions of ecological dynamics are significantly improved compared to outcomes of typical models that hold interaction strengths constant. We compared how well models based on different functions of neighbor density and identity did in describing population trajectories (i.e., persistence over time) and community dynamics (i.e., temporal stability, synchrony and degree of oscillation) in simulated two-species communities and a real diverse annual plant system. In our simulated communities, we found the highest level of coexistence between species pairs when species interactions varied from competitive to facilitative according to neighbor density (i.e., following a sigmoid function). Introducing within-guild facilitation through a nonlinear bounded function allowed populations, both simulated and empirical, to avoid extinction or runaway growth. In fact, nonlinear bounded functions (i.e., exponential and sigmoid functions) predicted population trends over time within the range of abundances observed over the last 10 years. With the sigmoid function, the simulated communities of two species displayed a higher probability of synchrony and oscillation than other functional forms. These simulated communities did not always show temporal stability but were predicted to coexist. Overall, varying species interactions lead to realistic ecological trajectories and community dynamics when bounded by asymptotes based on neighbor density. These findings are important for advancing our understanding of how diverse communities are sustained and for operationalizing ecological theory in the study of the real world.

ecology↗

bioRxiv2023

Climate change decreases the likelihood of tropical forest community persistence with a strong mediation of plant-plant network structures

Climate change is known to negatively impact tropical forests; yet how climate change impacts tree community persistence at local scales remains less clear. Using data from a long-term tropical forest census plot over 25 years, we constructed plant- plant interaction networks based on tree growth. We then quantified community persistence as feasibility domain of constituent species using recently developed frameworks of structural stability. We found a decrease in structural stability under warming and precipitation changes over time as evidenced by both direct environmental effects and indirect effects via network structure; and indirect effects were stronger than direct effects. Among these structures, facilitation:competition degree ratio and competitive transitivity were most positively related with structural stability. Our study highlights how the lens of plant-plant interaction networks can identify novel details about risk to tropical forest diversity under climate change at local scales. Insights from this work will be helpful for aligning forest management activities with areas under the greatest risk of species loss.

ecology↗

bioRxiv2023

Non-destructive spatial mapping of vegetation plots: a re-introduction of the pantograph

O_LINon-destructive spatial mapping of herbaceous plants is often not possible with many modern imaging techniques, especially in systems with highly structured, dense herbaceous canopies. For this purpose we suggest using a modern version of the classic pantograph, a simple instrument that allows precisely scaled drawings. The pantograph version we describe here was specifically designed for small-scale herbaceous vegetation mapping. C_LIO_LISpecifically, our pantograph design is useful for rapidly collecting accurate, spatially explicit data at the scale of 0.1-2 m2 and includes a paired drawing board for easy use in field conditions. C_LIO_LIWe tested the design and technique on 100 annual plant plots that ranged in total density and in plant stature. Based on this mapping trial, we present guidelines for effective manual mapping and map digitization. C_LIO_LIA pantograph is a useful and inexpensive to make tool for non-destructively spatially mapping individual herbaceous plants in the field. Here, we present instructions for the design and fabrication of our modern pantograph, board, and pencil attachment designed specifically for researchers wanting to include small-scale spatial context in their research. C_LI

ecology↗

bioRxiv2023

Environmental context, parameter sensitivity and structural sensitivity impact predictions of annual-plant coexistence

Predicting the outcome of interactions between species is central to our current understanding of diversity maintenance. However, we have limited information about the robustness of many model-based predictions of species coexistence. This limitation is partly because several sources of uncertainty are often ignored when making predictions. Here, we introduce a framework to simultaneously explore how different mathematical models, different environmental contexts, and parameter uncertainty impact the probability of predicting species coexistence. Using a set of pairwise competition experiments on annual plants, we provide direct evidence that subtle differences between models lead to contrasting predictions of both coexistence and competitive exclusion. We also show that the effects of environmental context-dependency and parameter uncertainty on predictions of species coexistence are not independent of the model used to describe population dynamics. Our work suggests that predictions of species coexistence and extrapolations thereof may be particularly vulnerable to these underappreciated founts of uncertainty.

ecology↗

bioRxiv2022

Estimating interaction matrices from performance data for diverse systems

O_LINetwork theory allows us to understand complex systems by evaluating how their constituent elements interact with one another. Such networks are built from matrices which describe the effect of each element on all others. Quantifying the strength of these interactions from empirical data can be difficult, however, because the number of potential interactions increases non-linearly as more elements are included in the system, and not all interactions may be empirically observable when some elements are rare. C_LIO_LIWe present a novel modelling framework which estimates the strength of pairwise interactions in diverse horizontal systems, using measures of species performance in the presence of varying densities of their potential interaction partners. C_LIO_LIOur method allows us to directly estimate pairwise effects when they are statistically identifiable and approximate pairwise effects when they would otherwise be statistically unidentifiable. The resulting interaction matrices can include positive and negative effects, the effect of a species on itself, and are non-symmetrical. C_LIO_LIThe advantages of these features are illustrated with a case study on an annual wildflower community of 22 focal and 52 neighbouring species, and a discussion of potential applications of this framework extending well beyond plant community ecology. C_LI

ecology↗

bioRxiv2021

Disentangling key species interactions in diverse and heterogeneous communities: A Bayesian sparse modeling approach

1Modeling species interactions in diverse communities traditionally requires a prohibitively large number of species-interaction coefficients, especially when considering environmental dependence of parameters. We implemented Bayesian variable selection via sparsity-inducing priors on non-linear species abundance models to determine which species-interactions should be retained and which can be represented as an average heterospecific interaction term, reducing the number of model parameters. We evaluated model performance using simulated communities, computing out-of-sample predictive accuracy and parameter recovery across different input sample sizes. We applied our method to a diverse empirical community, allowing us to disentangle the direct role of environmental gradients on species intrinsic growth rates from indirect effects via competitive interactions. We also identified a few neighboring species from the diverse community that had non-generic interactions with our focal species. This sparse modeling approach facilitates exploration of species-interactions in diverse communities while maintaining a manageable number of parameters.

ecology↗

bioRxiv2020

The role of higher-order biotic interactions on tropical tree growth

Growth in individual size or biomass is a key demographic component in population models, with wide-ranging applications from quantifying species performance across abiotic or biotic conditions to assessing landscape-level dynamics under global change. In forest ecology, the responses of tree growth to biotic interactions are widely held to be crucial for understanding forest diversity, function, and structure. To date, most studies on plant-plant interactions only examine the additive competitive or facilitative interactions between species pairs; however, there is increasing evidence of non-additive, higher-order interactions (HOIs) impacting species demographic rates. When HOIs are present, the dynamics of a multi-species community cannot be fully understood or accurately predicted solely from pairwise outcomes because of how additional species interfere with the direct, pairwise interactions. Such HOIs should be particularly prevalent where species show nonlinear functional responses to resource availability and resource-acquisition traits themselves are density dependent. With this in mind, we used data from a tropical secondary forest--a system that fulfills both of these conditions--to build a ontogenetic diameter-growth model for individuals across ten woody-plant species. We allowed both direct and indirect interactions within communities to influence the species-specific growth parameters in a generalized Lotka-Volterra model. Specifically, indirect interactions entered the model as higher-order quadratic terms, i.e. non-additive effects of conspecific and heterospecific neighbour size on the focal individuals growth. For the whole community and for four out of ten focal species, the model that included HOIs had more statistical support than the model that included only direct interactions, despite the former containing a far greater number of parameters. HOIs had comparable effect sizes to direct interactions, and tended to further reduce the diameter growth rates of most species beyond what direct interactions had already reduced. In a simulation of successional stand dynamics, the inclusion of HOIs lead to rank swaps in species diameter hierarchies, even when community-level size distributions remained qualitatively similar. Our study highlights the implications, and discusses possible mechanisms, of non-additive density dependence in highly diverse and light-competitive tropical forests.

ecology↗

bioRxiv2020

Aridity drives coordinated trait shifts but not decreased trait variance across the geographic range of eight Australian trees

ContextLarge intraspecific functional trait variation strongly impacts many aspects of natural communities and ecosystems, yet is inconsistent across traits and species. ApproachWe measured within-species variation in leaf mass per area (LMA), leaf dry matter content (LDMC), branch wood density (WD), and allocation to stem area vs. leaf area in branches (branch Huber value, HV) across the aridity range of seven Australian eucalypts and an Acacia species to explore how traits and their variances change with aridity. Results and ConclusionsWithin-species, we found consistent increases in LMA, LDMC and WD, and HV with increasing aridity, resulting in consistent trait coordination across tissues. However, this coordination only emerged across sites with large climate differences. Unlike trait means, patterns of trait variance with aridity were mixed across populations and species and showed limited support for constrained trait variation in dryer populations or more xeric species. SynthesisOur results highlight that climate can drive consistent within-species trait patterns, but that these patterns might often be obscured by the complex nature of morphological traits and sampling incomplete species ranges or sampling confounded stress gradients.

ecology↗

bioRxiv2018

The filtering metaphor revisited: competition and environment jointly structure invasibility and coexistence

Filtering, or the reduction in species diversity that occurs because not all species can persist in all locations, is thought to unfold hierarchically, at large scales due to the environment and at small scales due to competition. However, the ecological effects of competition and the environment are not independent, and observational approaches preclude investigation into their interplay. We use a demographic approach with 30 plant species to experimentally test (i) the effect of competition on species persistence in two soil moisture environments, and (ii) the effect of environmental conditions on the mechanisms underlying competitive coexistence. We find that competitors cause differential persistence of species across environments even when these effects are lacking in the absence of competition, and that the traits that determine persistence depend on the competitive environment. Changing environmental conditions generated idiosyncratic effects on coexistence outcomes, increasing competitive exclusion of some species while promoting coexistence of others. Our results highlight the importance of considering environmental filtering in light of, rather than in isolation from, competition, and challenge community assembly models and approaches to projecting future species distributions.

ecology↗