An Empiricist's Guide to Using Ecological Theory.

AbstractA scientific understanding of the biological world arises when ideas about how nature works are formalized, tested, refined, and then tested again. Although the benefits of feedback between theoretical and empirical research are widely acknowledged by ecologists, this link is still not as strong as it could be in ecological research. This is in part because theory, particularly when expressed mathematically, can feel inaccessible to empiricists who may have little formal training in advanced math. To address this persistent barrier, we provide a general and accessible guide that covers the basic, step-by-step process of how to approach, understand, and use ecological theory in empirical work. We first give an overview of how and why mathematical theory is created, then outline four specific ways to use both mathematical and verbal theory to motivate empirical work, and finally present a practical tool kit for reading and understanding the mathematical aspects of ecological theory. We hope that empowering empiricists to embrace theory in their work will help move the field closer to a full integration of theoretical and empirical research.

The effects of ecological selection on species diversity and trait distribution: predictions and an empirical test.

Ecological selection is a major driver of community assembly. Selection is classified as stabilizing when species with intermediate trait values gain the highest reproductive success, whereas selection is considered directional when fitness is highest for species with extreme trait values. Previous studies have investigated the effects of different selection types on trait distribution, but the effects of selection on species diversity have remained unclear. Here, we propose a framework for inferring the type and strength of selection by studying species diversity and trait distribution together against null expectations. We use a simulation model to confirm our prediction that directional selection should lead to lower species diversity than stabilizing selection despite a similar effect on trait community-weighted variance. We apply the framework to a mesocosm system of annual plants to test whether differences in species diversity between two habitats that vary in productivity are related to differences in selection on seed mass. We show that, in both habitats, species diversity was lower than the null expectation, but that species diversity was lower in the more productive habitat. We attribute this difference to strong directional selection for large-seeded species in the productive habitat as indicated by trait community-weighted mean being higher and community-weighted variance being lower than the null expectations. In the less productive habitat, we found that community-weighted variance was higher than expected by chance, suggesting that seed mass could be a driver of niche partitioning under such conditions. Altogether, our results suggest that viewing species diversity and trait distribution as interrelated patterns driven by the same process, ecological selection, is helpful in understanding community assembly.

Reconstructing large interaction networks from empirical time series data.

Reconstructing interactions from observational data is a critical need for investigating natural biological networks, wherein network dimensionality is usually high. However, these pose a challenge to existing methods that can quantify only small interaction networks. Here, we proposed a novel approach to reconstruct high-dimensional interaction Jacobian networks using empirical time series without specific model assumptions. This method, named "multiview distance regularised S-map," generalised the state space reconstruction to accommodate high dimensionality and overcome difficulties in quantifying massive interactions with limited data. When evaluating this method using time series generated from theoretical models involving hundreds of interacting species, estimated strengths of interaction Jacobians were in good agreement with theoretical expectations. Applying this method to a natural bacterial community helped identify important species from the interaction network and revealed mechanisms governing the dynamical stability of a bacterial community. The proposed method overcame the challenge of high dimensionality in large natural dynamical systems.

The Temporal Dimension of Plant-Soil Microbe Interactions: Mechanisms Promoting Feedback between Generations.

AbstractSoil microbes can influence plant competitive outcomes by stabilizing plant community dynamics or mediating plant competitive hierarchies. Which effect dominates depends on whether microbial effects can extend beyond the focal conditioning individual. While it is well known that microbial effects can extend to other individuals through space, we lack an explicit theoretical understanding of the factors that regulate their spread to other individuals in subsequent generations. Here, we examine how the commonly assumed stabilizing effects of host-specific pathogens in fact depend on two factors that allow microbial effects to be cross-generational-which plant demographic vital rate is influenced by microbes and the conditioning and decay rates of soil microbial communities. With a novel patch occupancy model that incorporates the transition of soil states following plant colonization and mortality, we show that host-specific pathogens enable plant coexistence when they suppress conspecific plant colonization of empty patches but contribute to competitive hierarchies when they modify only the mortality and fecundity of the conditioning plant individual. In a series of model extensions, we further demonstrate that these latter microbial effects can still promote coexistence, but only when microbial communities decay slowly following plant death, thereby allowing microbial effects to be cross-generational. Our study calls for further empirical work quantifying the demographic rates most affected by soil microbes as well as the timescales of conditioning and decay.

Age-specific habitat preference, carrying capacity, and landscape structure determine the response of population spatial variability to fishing-driven age truncation.

Understanding the mechanisms underlying spatial variability of exploited fish is critical for the sustainable management of fish stocks. Empirical studies suggest that size-selective fishing can elevate fish population spatial variability (i.e., more heterogeneous distribution) through age truncation, making the population less resilient to changing environment. However, species differ in how their spatial variability responds to age truncation and the underlying mechanisms remain unclear.We hypothesize that age-specific habitat preference, together with environmental carrying capacity and landscape structure, determines the response of population spatial variability to fishing-induced age truncation. To test these hypotheses, we design an individual-based model of an age-structured fish population on a two-dimensional landscape under size-selective fishing. Individual fish reproduces and survives, and moves between habitats according to age-specific habitat preference and density-dependent habitat selection.Population spatial variability elevates with increasing age truncation, and the response is stronger for populations with stronger age-specific habitat preference. On a gradient landscape, reducing carrying capacity elevates the relative importance of density dependence in habitat selection, which weakens the response of spatial variability to age truncation for populations with strong age-specific habitat preference. On a fragmented landscape, both populations with strong and weak age-specific habitat preferences are restricted at local optimal habitats, and reducing carrying capacity weakens the responses of spatial variability to age truncation for both populations. Synthesis and applications. We demonstrate that to track and predict the changes in population spatial variability under exploitation, it is essential to consider the interactive effects of age-specific habitat preference, carrying capacity, and landscape structure. To improve spatial management in fisheries, it is crucial to enhance empirical and theoretical developments in the methodology to quantify age-specific habitat preference of marine fish, and to understand how climatic change influences carrying capacity and landscape continuity.

Dynamic plant-soil microbe interactions: the neglected effect of soil conditioning time.

Plant-soil feedback (PSF) may change in strength over the life of plant individuals as plants continue to modify the soil microbial community. However, the temporal variation in PSF is rarely quantified and its impacts on plant communities remain unknown. Using a chronosequence reconstructed from annual aerial photographs of a coastal dune ecosystem, we characterized > 20-yr changes in soil microbial communities associated with individuals of the four dominant perennial species, one legume and three nonlegume. We also quantified the effects of soil biota on conspecific and heterospecific seedling performance in a glasshouse experiment that preserved soil properties of these individual plants. Additionally, we used a general individual-based model to explore the potential consequences of temporally varying PSF on plant community assembly. In all plant species, microbial communities changed with plant age. However, responses of plants to the turnover in microbial composition depended on the identity of the seedling species: only the soil biota effect experienced by the nonlegume species became increasingly negative with longer soil conditioning. Model simulation suggested that temporal changes in PSF could affect the transient dynamics of plant community assembly. These results suggest that temporal variation in PSF over the life of individual plants should be considered to understand how PSF structures plant communities.

Author Correction: A global test of ecoregions.

The original paper was published without unique DOIs for GBIF occurrence downloads. These have now been inserted as references 70-76, and the error has been corrected in the PDF and HTML versions of the article.

A global test of ecoregions.

A foundational paradigm in biological and Earth sciences is that our planet is divided into distinct ecoregions and biomes demarking unique assemblages of species. This notion has profoundly influenced scientific research and environmental policy. Given recent advances in technology and data availability, however, we are now poised to ask whether ecoregions meaningfully delimit biological communities. Using over 200 million observations of plants, animals and fungi we show compelling evidence that ecoregions delineate terrestrial biodiversity patterns. We achieve this by testing two competing hypotheses: the sharp-transition hypothesis, positing that ecoregion borders divide differentiated biotic communities; and the gradual-transition hypothesis, proposing instead that species turnover is continuous and largely independent of ecoregion borders. We find strong support for the sharp-transition hypothesis across all taxa, although adherence to ecoregion boundaries varies across taxa. Although plant and vertebrate species are tightly linked to sharp ecoregion boundaries, arthropods and fungi show weaker affiliations to this set of ecoregion borders. Our results highlight the essential value of ecological data for setting conservation priorities and reinforce the importance of protecting habitats across as many ecoregions as possible. Specifically, we conclude that ecoregion-based conservation planning can guide investments that simultaneously protect species-, community- and ecosystem-level biodiversity, key for securing Earth's life support systems into the future.

Coexistence theory and the frequency-dependence of priority effects.

Priority effects are commonly used to describe a broad suite of phenomena capturing the influence of species arrival order on the diversity, composition and function of ecological communities. Several studies have suggested reframing priority effects around the stabilizing and equalizing concepts of coexistence theory. We show that the only compatible priority effects are those characterized by positive frequency-dependence, irrespective of whether they emerge in equilibrium or non-equilibrium systems.

Species coexistence through simultaneous fluctuation-dependent mechanisms.

Understanding the origins and maintenance of biodiversity remains one of biology's grand challenges. From theory and observational evidence, we know that variability in environmental conditions through time is likely critical to the coexistence of competing species. Nevertheless, experimental tests of fluctuation-driven coexistence are rare and have typically focused on just one of two potential mechanisms, the temporal storage effect, to the neglect of the theoretically equally plausible mechanism known as relative nonlinearity of competition. We combined experiments and simulations in a system of nectar yeasts to quantify the relative contribution of the two mechanisms to coexistence. Resource competition models parameterized from single-species assays predicted the outcomes of mixed-culture competition experiments with 83% accuracy. Model simulations revealed that both mechanisms have measurable effects on coexistence and that relative nonlinearity can be equal or greater in magnitude to the temporal storage effect. In addition, we show that their effect on coexistence can be both antagonistic and complementary. These results falsify the common assumption that relative nonlinearity is of negligible importance, and in doing so reveal the importance of testing coexistence mechanisms in combination.

Incorporating the soil environment and microbial community into plant competition theory.

Plants affect microbial communities and abiotic properties of nearby soils, which in turn influence plant growth and interspecific interaction, forming a plant-soil feedback (PSF). PSF is a key determinant influencing plant population dynamics, community structure, and ecosystem functions. Despite accumulating evidence for the importance of PSF and development of specific PSF models, different models are not yet fully integrated. Here, we review the theoretical progress in understanding PSF. When first proposed, PSF was integrated with various mathematical frameworks to discuss its influence on plant competition. Recent theoretical models have advanced PSF research at different levels of ecological organizations by considering multiple species, applying spatially explicit simulations to examine how local-scale predictions apply to larger scales, and assessing the effect of PSF on plant temporal dynamics over the course of succession. We then review two foundational models for microbial- and litter-mediated PSF. We present a theoretical framework to illustrate that although the two models are typically presented separately, their behavior can be understood together by invasibility analysis. We conclude with suggestions for future directions in PSF theoretical studies, which include specifically addressing microbial diversity to integrate litter- and microbial-mediated PSF, and apply PSF to general coexistence theory through a trait-based approach.

The soil microbial community predicts the importance of plant traits in plant-soil feedback.

Reciprocal interaction between plant and soil (plant-soil feedback, PSF) can determine plant community structure. Understanding which traits control interspecific variation of PSF strength is crucial for plant ecology. Studies have highlighted either plant-mediated nutrient cycling (litter-mediated PSF) or plant-microbe interaction (microbial-mediated PSF) as important PSF mechanisms, each attributing PSF variation to different traits. However, this separation neglects the complex indirect interactions between the two mechanisms. We developed a model coupling litter- and microbial-mediated PSFs to identify the relative importance of traits in controlling PSF strength, and its dependency on the composition of root-associated microbes (i.e. pathogens and/or mycorrhizal fungi). Results showed that although plant carbon: nitrogen (C : N) ratio and microbial nutrient acquisition traits were consistently important, the importance of litter decomposability varied. Litter decomposability was not a major PSF determinant when pathogens are present. However, its importance increased with the relative abundance of mycorrhizal fungi as nutrient released from the mycorrhizal-enhanced litter production to the nutrient-depleted soils result in synergistic increase of soil nutrient and mycorrhizal abundance. Data compiled from empirical studies also supported our predictions. We propose that the importance of litter decomposability depends on the composition of root-associated microbes. Our results provide new perspectives in plant invasion and trait-based ecology.