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Species coexistence attracts wide interest in ecology. Modern coexistence theory (MCT) identifies coexistence mechanisms, one of which, storage effects, hinges on relationships between fluctuations in environmental and competitive pressures. However, such relationships are typically measured using covariance, which does not account for the possibility that environment and competition may be more related to each other when they are strong than when weak, or vice versa. Recent work showed that such 'asymmetric tail associations' (ATAs) are common between ecological variables, and are important for extinction risk, ecosystem stability, and other phenomena. We extend MCT, decomposing storage effects to show the influence of ATAs. Analysis of a simple model and an empirical example using diatoms illustrate that ATA influences can be comparable in magnitude to other mechanisms of coexistence and that ATAs can make the difference between species coexistence and competitive exclusion. ATA influences may be an important new mechanism of coexistence., (© 2023 John Wiley & Sons Ltd.)

Taylor's law (TL), a commonly observed and applied pattern in ecology, describes variances of population densities as related to mean densities via log(variance) = log(a) + b*log(mean). Variations among datasets in the slope, b, have been associated with multiple factors of central importance in ecology, including strength of competitive interactions and demographic rates. But these associations are not transparent, and the relative importance of these and other factors for TL slope variation is poorly studied. TL is thus a ubiquitously used indicator in ecology, the understanding of which is still opaque. The goal of this study was to provide tools to help fill this gap in understanding by providing proximate determinants of TL slopes, statistical quantities that are correlated to TL slopes but are simpler than the slope itself and are more readily linked to ecological factors. Using numeric simulations and 82 multi-decadal population datasets, we here propose, test and apply two proximate statistical determinants of TL slopes which we argue can become key tools for understanding the nature and ecological causes of TL slope variation. We find that measures based on population skewness, coefficient of variation and synchrony are effective proximate determinants. We demonstrate their potential for application by using them to help explain covariation in slopes of spatial and temporal TL (two common types of TL). This study provides tools for understanding TL, and demonstrates their usefulness., (© 2018 The Authors. Journal of Animal Ecology © 2018 British Ecological Society.)

Phytoplankton are key components of aquatic ecosystems, fixing CO2 from the atmosphere through photosynthesis and supporting secondary production, yet relatively little is known about how future global warming might alter their biodiversity and associated ecosystem functioning. Here, we explore how the structure, function, and biodiversity of a planktonic metacommunity was altered after five years of experimental warming. Our outdoor mesocosm experiment was open to natural dispersal from the regional species pool, allowing us to explore the effects of experimental warming in the context of metacommunity dynamics. Warming of 4°C led to a 67% increase in the species richness of the phytoplankton, more evenly-distributed abundance, and higher rates of gross primary productivity. Warming elevated productivity indirectly, by increasing the biodiversity and biomass of the local phytoplankton communities. Warming also systematically shifted the taxonomic and functional trait composition of the phytoplankton, favoring large, colonial, inedible phytoplankton taxa, suggesting stronger top-down control, mediated by zooplankton grazing played an important role. Overall, our findings suggest that temperature can modulate species coexistence, and through such mechanisms, global warming could, in some cases, increase the species richness and productivity of phytoplankton communities.

Temperature is a key driver of ecological processes and patterns. The ramifications of temperature for ecological communities include not only its direct effects on the physiology of individuals, but also how these effects play out in the context of other processes such as competition. Apparently idiosyncratic or difficult to predict effects of temperature on competitive outcomes are well represented in the literature. General theoretical understanding of how physiological influences of temperature filter through community dynamics to determine outcomes is limited. We present a theoretical framework for predicting the effects of temperature on competition among species, based on understanding the effects of temperature on the physiological and population parameters of the species. The approach helps unify formal resource competition theory with metabolic and physiological ecology. Phytoplankton and many other ectotherms are smaller at higher temperatures. This has been observed experimentally, across geographical gradients, and as change accompanying climate warming, but it has not been explained in terms of competition. As a case study, we apply our theoretical framework to competition for nutrients among differently sized phytoplankton. Based on this analysis, we hypothesize that the prevalence of smaller phytoplankton at higher temperatures is at least partly due to an accentuated competitive advantage of smaller cells at higher temperatures with respect to nutrient uptake and growth. We examine the scope for extending the approach to understand resource competition, generally, among ectotherms of different sizes., (© 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.)

Landscape ecology plays a vital role in understanding the impacts of land-use change on biodiversity, but it is not a predictive discipline, lacking theoretical models that quantitatively predict biodiversity patterns from first principles. Here, we draw heavily on ideas from phylogenetics to fill this gap, basing our approach on the insight that habitat fragments have a shared history. We develop a landscape 'terrageny', which represents the historical spatial separation of habitat fragments in the same way that a phylogeny represents evolutionary divergence among species. Combining a random sampling model with a terrageny generates numerical predictions about the expected proportion of species shared between any two fragments, the locations of locally endemic species, and the number of species that have been driven locally extinct. The model predicts that community similarity declines with terragenetic distance, and that local endemics are more likely to be found in terragenetically distinctive fragments than in large fragments. We derive equations to quantify the variance around predictions, and show that ignoring the spatial structure of fragmented landscapes leads to over-estimates of local extinction rates at the landscape scale. We argue that ignoring the shared history of habitat fragments limits our ability to understand biodiversity changes in human-modified landscapes., (© 2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.)

A major goal of ecology is to discover how dynamics and structure of multi-trophic ecological communities are related. This is difficult, because whole-community data are limited and typically comprise only a snapshot of a community instead of a time series of dynamics, and mathematical models of complex system dynamics have a large number of unmeasured parameters and therefore have been only tenuously related to real systems. These are related problems, because long time-series, if they were commonly available, would enable inference of parameters. The resulting 'plague of parameters' means most studies of multi-species population dynamics have been very theoretical. Dynamical models parametrized using physiological allometries may offer a partial cure for the plague of parameters, and these models are increasingly used in theoretical studies. However, physiological allometries cannot determine all parameters, and the models have also rarely been directly tested against data. We confronted a model of community dynamics with data from a lake community. Many important empirical patterns were reproducible as outcomes of dynamics, and were not reproducible when parameters did not follow physiological allometries. Results validate the usefulness, when parameters follow physiological allometries, of classic differential-equation models for understanding whole-community dynamics and the structure-dynamics relationship.

1. The spectral colour of population dynamics and its causes have attracted much interest. The spectral colour of a time series can be determined from its power spectrum, which shows what proportion of the total variance in the time series occurs at each frequency. A time series with a red spectrum (a negative spectral exponent) is dominated by low-frequency oscillations, and a time series with a blue spectrum (a positive spectral exponent) is dominated by high-frequency oscillations. 2. Both climate variables and population time series are characterised by red spectra, suggesting that a population's environment might be partly responsible for its spectral colour. Laboratory experiments and models have been used to investigate this potential link. However, no study using field data has directly tested whether populations in redder environments are redder. 3. This study uses the Global Population Dynamics Database together with climate data to test for this effect. We found that the spectral exponent of mean summer temperatures correlates positively and significantly with population spectral exponent. 4. We also found that over the last century, temperature climate variables on most continents have become bluer. 5. Although population time series are not long or abundant enough to judge directly whether their spectral colours are changing, our two results taken together suggest that population spectral colour may be affected by the changing spectral colour of climate variables. Population spectral colour has been linked to extinction; we discuss the potential implications of our results for extinction probability., (© 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.)

Individuals tend to interact more strongly with nearby individuals or within particular social groups. Recent theoretical advances have demonstrated that these within-population relationships can have fundamental implications for ecological and evolutionary dynamics. In particular, contact networks are crucial to the spread and evolution of disease. However, the theory remains largely untested experimentally. Here, we manipulate habitat viscosity and thereby the frequency of local interactions in an insect-pathogen model system in which the virus had previously been shown to have little effect on host population dynamics. At high viscosity, the pathogen caused the collapse of dominant and otherwise stable host generation cycles. Modeling shows that this collapse can be explained by an increase in the frequency of intracohort interactions relative to intercohort interactions, leading to more disease transmission. Our work emphasizes that spatial structure can subtly mediate intraspecific competition and the effects of natural enemies. A decrease in dispersal in a population may actually (sometimes rather counterintuitively) intensify the effects of parasites. Broadly, because anthropological and environmental change often cause changes in population mixing, our work highlights the potential for dramatic changes in the effects of parasites on host populations.

Predicting species population density-body mass scaling in community food webs (henceforth webs) is important for conservation and to understand community structure. Very different types of scaling have been studied, based on either individuals or species. The individual size distribution (ISD) describes the distribution of individual-organism body masses regardless of taxonomy, and contains the same information as the abundance spectrum. Focusing instead on species, the local size-density relationship (LSDR) plots population densities vs. mean body masses of species. The distribution of species mean body masses (the species-mean-size distribution, SMSD) is also important but previously little studied in webs. We here combine and formalize theory of several authors to predict: how these three descriptions are related; the forms of the LSDR and ISD; and variation in scaling among webs. We describe empirically the SMSDs of two pelagic, one estuarine, and 146 soil webs by power laws and generalizations. We test theory and find it broadly validated.

Populations fluctuate because of their internal dynamics, which can be nonlinear and stochastic, and in response to environmental variation. Theory predicts how the colour of environmental stochasticity affects population means, variances and correlations with the environment over time. The theory has not been tested for cycling populations, commonly observed in field systems. We applied noise of different colours to cycling laboratory beetle populations, holding other statistical properties of the noise fixed. Theory was largely validated, but failed to predict observations in sufficient detail. The main period of population cycling was shifted up to 33% by the colour of environmental stochasticity. Noise colour affected population means, variances and dominant periodicities differently for populations that cycled in different ways without noise. Our results show that changes in the colour of climatic variability, partly caused by humans, may affect the main periodicity of cycling populations, possibly impacting industry, pest management and conservation.